The main purpose of this study was to determine the size and direction of the seasonal dynamics of organic carbon (Сmicro) and nitrogen (Nmicro) biomass of microorganisms and microbial index (Cmicro : Corg) of natural and agrocenoses with their different uses. Field research methods involved taking of soil samples in 0-10-, 10-20- and 20-40 сm layers. Under laboratory conditions, the content of total soil carbon was determined by dry oxygen combustion on a Vario EL III analyzer (Elementar Analyzensysteme, Hanau, Germany). The carbon content of microbial biomass (Сmicro) was determined by chloroform fumigation extraction method (CFE). To freshly taken soil samples (2 hours) and soil samples after their 24-hour fumigation with chloroform vapors, 0.5 M K2SO4 was added to extract biomass lysis products of soil microorganisms. The content of organic carbon and nitrogen in the biomass of microorganisms in the obtained filtrates was determined on the Elementar Liqui TOC II, Analyzensysteme GmbH, Germany. The carbon content of microbial biomass was calculated from the difference between carbon in fumigated and control samples using a factor of 0,45 - for carbon and 0,54 – for nitrogen. The microbial index of soils was determined by the ratio between the carbon of microorganisms and the total organic carbon of the soil – Cmicro : Corg • 100 (%). Average values and confidence intervals were determined for each defined indicator. The Bonferoni method was used to correct the errors of multiple comparative samples of a one-way ANOVA analyze. K. Pearson’s linear correlation analysis was used to establish the relationships between the dynamics of carbon biomass of microorganisms and organic carbon of the soil during the growing season. Our research has shown the dynamics of Сmicro, Nmicro, Сmicro : Nmicro and Cmicro : Corg during the growing season. Analysis of the box plot showed the largest amplitude of Сmicro changes in the upper 0-10 cm layer of izogumusol. The smallest difference in the quartile range (IQR0,25-0,75) was for no-till and overhang (Ab) in the upper 0-10-, no-till (NT) and fallow (F) - in the layer 10-20- and plowing (CT) - in a layer of 20-40 cm. The content of organic carbon biomass of microorganisms in the upper layer of izogumusol at the beginning of the growing season had the highest values of Ab (577,79  1,64 mg/kg), NT (485,43  1,97 mg/kg) and CT (470,43  0,77 mg/kg), the smallest - for F (370,15  2,18 mg/kg). The content of Nmicro during this period decreased from Ab to Comb (combined tillage), NT, CT, Rot (rotary tillage), RT (reduced (ridge) tillage) and F, respectively. In the 20-40 cm layer, the highest values of Сmicro and Nmicro were observed in mid-July. The lowest values of Сmicro and Nmicro and the largest – Сmicro : Nmicro were found in late August for all variants and layers of the study. The dynamics of the microbial index resembled the trends of Сmicro and Nmicro. The largest share of Smicro in Sorghum during the growing season, on average was: - Ab (1,82  1,85 %) and NT (1,66  1,52 %) - in the layer 0-10-, - Ab (1,23  1,27 %) and NT (1,29  1,32 %) - in the layer 10-20- and - Ab (1,19  1,09 %) and F (1,11  1,077 %) - in a layer of 20-40 cm. Different use of izogumusol affected the amplitude of seasonal changes of Сmicro and Nmicro and did not affect on their direction. The maximum content of Сmicro and Nmicro was observed at the beginning of the growing season - in a layer of 0-10 cm and in mid-July - in a layer of 20-40 cm, the minimum - at the end of the summer period. During this period, the widest ratio of Сmicro : Nmicro was for F and CT - in the layer 0-20 cm and CT and Rot - in the layer 20-40 cm. The Pearson’s correlation coefficient between Сmicro and Corg increased from the upper 0-10- to the lower 20-40 cm layer of izogumusol. "Strong" and "high" negative correlations have been established between Сmicro and Corg, but no pattern has been found between the correlation coefficient and tillage technologies.

Copernicus is Europe's space-based Earth monitoring asset, which consists of a complex set of systems that collect data from different sources: remote sensing satellites (RS) and in-situ sensors such as ground stations, airborne and marine sensors. This study was originally prepared for the needs of the Czech agricultural community, where we provided an in-depth analysis of articles related to Earth observation in precision agriculture. At a later stage, we extended this study by comparing the recommendations of the European EO4Agri project and scientific articles published in MDPI. We had two important objectives, one was to validate the results of the EO4Agri project and the other was to look for gaps in current research and community needs. To recognize the importance of using Sentinel 1 data, we also added a specific analysis of methods for data fusion of Sentinel 1 and Sentinel 2 data.

Zagros is an important region with high quality and quantity karstic water resources in the Middle East. This region provides a dominant part of potable and agricultural water needs for its inhabitants as well as agricultural water needs for nearby regions. Therefore, studying karstic water resources in Zagros by accurate methods such as stable isotopes techniques is very important. In this investigation, hydrological characteristics of groundwater resources including groundwater origin, recharge rate and recharge elevation have been studied using stable isotopes (¹⁸O and ²H). The results show that stable isotopes signatures in groundwater resources show notable variations across Zagros and groundwater resource mainly plot on south and west Zagros meteoric water lines. In addition, recharge elevation and recharge rate in groundwater resources also show significant variations in Zagros. Finally, the stable isotopes signatures in precipitation and groundwater has been used to study the role of each dominant air mass (contribution percentage of precipitation events originate from each air mass) in groundwater resources recharge using Simmr package in R language. Overall, groundwater resources in Zagros is recharged by precipitation events originate from various air masses and they have various recharge rates and recharge elevations.

The efficacy of predicting geochemical parameters with a 2-chain workflow using spectral data as the initial input is evaluated. Spectral measurements spanning the approximate 400-25000nm spectral range are used to train a workflow consisting of a non-negative matrix function (NMF) step, for data reduction, and a random forest regression (RFR) to predict 8 geochemical parameters. Approximately 175000 spectra with their corresponding chemical analysis were available for training, testing and validation purposes. The samples and their spectral and chemical parameters represent 9399 drillcore. Of those, approximately 20000 spectra and their accompanying analysis were used for training and 5000 for model validation. The remaining pairwise data (150000 samples) were used for testing of the method. The data are distributed over 2 large spatial extents (980 km2 and 3025 km2 respectively) and allowed the proposed method to be tested against samples that are spatially distant from the initial training points. Global R2 scores and wt.% RMSE on the 150000 validation samples are Fe(0.95/3.01), SiO2(0.96/3.77), Al2O3(0.92/1.27), TiO(0.68/0.13), CaO(0.89/0.41), MgO(0.87/0.35), K2O(0.65/0.21) and LOI(0.90/1.14), given as Parameter(R2/RMSE), and demonstrate that the proposed method is capable of predicting the 8 parameters and is stable enough, in the environment tested, to extend beyond the training sets initial spatial location.

This study provides a thorough review and analysis of the evolution of the Greek vehicle fleet over the last ~30 years, which is next used for the generation of high granularity fleet projections and for the estimation of relevant environmental benefits by 2030. The integrated methodology developed takes also into account vehicle clustering and the Brown’s Double Simple Exponential Smoothing technique that together with the adoption of COPERT based emission factors allow for the estimation of the anticipated emissions in 2030. Expected 2030 emissions levels suggest a reduction across all pollutants in comparison to 2018, ranging from 3.7% for PM10 to 54.5% for NMVOC (and 46% for CO, 14% for SO2, 28% for NOX and 21% for CO2). We find that Greece is on track with national goals concerning the reduction of air pollution from the transportation sector, stressing the positive contribution of EVs and new, "greener" vehicles, and setting new challenges for the further improvement of the sector beyond the 2030 outlook.

Water is essential for all living things however its pain has become serious. Many industrial activities cause its pollution by the release of polluting byproduct. Waste water treatment is hence necessary. In this context, the waste water of the textile industry containing Red Acid 52 was treated by the solid waste of the washed natural phosphate byproduct. Natural phosphate was also studied. The solid materials were first characterized by chemical analysis, Fourier Transform Infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The phosphate materials were after that, tested in the adsorption of the Red Acid 52. The experimental data indicated that the phosphate waste rock allowed the removal of Red Acid 52. Its maximum retention capacity attained 18.4 mg.g-1. Calcinations of materials inhibits the removal capacity found reduced by 60 to 70%. The adsorption kinetics of the Red Acid 52 on the material is well described by the pseudo second order model while the adsorption isotherms are identified by the Langmuir model. Hereafter, the thermodynamic study revealed that the adsorption process is spontaneous and exothermic. Keywords: Waste water, Phosphate co-product, Adsorption, Red Acid 52.

As Christopher Alexander discovered, all space or matter – either organic or inorganic – has some degree of order in it according to its structure and arrangement. The order refers to a kind of structural character, called living structure, which is defined as a mathematical structure that consists of numerous substructures with an inherent hierarchy. Across the hierarchy, there are far more small substructures than large ones, while on each level of the hierarchy the substructures are more or less similar in size. In this paper we develop a new approach to representing geographic space as a hierarchy of recursively defined subspaces for computing the degree of order. A geographic space is first represented as a hierarchy of recursively defined subspaces, and all the subspaces are then topologically represented as a network for computing the degree of order of the geographic space, as well as that of its subspaces. Unlike conventional geographic representations, which are mechanical in nature, this new geographic representation is organic, conceived, and developed under the third view of space; that is, space is neither lifeless nor neutral, but a living structure capable of being more living or less living. Thus, the order can also be referred to as life, beauty, coherence, or harmony. We applied the new representation to three urban environments, 253 patterns, and 35 black-white strips to verify it and to demonstrate advantages of the new approach and the new kind of order. We further discuss the implications of the approach and the order on geographic information science and sustainable urban planning.

Currently available nationwide prediction models for fine particulate matter (PM_2.5) lack prediction confidence intervals and usually do not describe cross validated model performance at different spatiotemporal resolutions and extents. We used 41 different spatiotemporal predictors, including data on land use, meteorology, aerosol optical density, emissions, wildfires, population, traffic, and spatiotemporal indicators to train a machine learning model to predict daily averages of PM_2.5 concentrations at 0.75 sq km resolution across the contiguous United States from 2000 through 2020. We utilized a generalized random forest model that allowed us to generate asymptotically-valid prediction confidence intervals and took advantage of its usefulness as an ensemble learner to quickly and cheaply characterize leave-one-location-out CV model performance for different temporal resolutions and geographic regions. Using a variable importance metric, we selected 8 predictors that were able to accurately predict daily PM_2.5, with an overall leave-one-location-out cross validated median absolute error of 1.20 ug/m³, an R² of 0.84, and confidence interval coverage fraction of 95%. When considering aggregated temporal windows, the model achieved leave-one-location-out cross validated median absolute errors of 0.99, 0.76, 0.63, and 0.60 ug/m³ for weekly, monthly, annual, and all-time exposure assessments, respectively. We further describe the model’s cross validated performance at different geographic regions in the United States, finding that it performs worse in the Western half of the country where there are less monitors. The code and data used to create this model are publicly available and we have developed software packages to be used for exposure assessment. This accurate exposure assessment model will be useful for epidemiologists seeking to study the health effects of PM across the continental United States, while possibly considering exposure estimation accuracy and uncertainty specific to the the spatiotemporal resolution and extent of their study design and population.

: Foodshed approaches allow the assessment of the theoretical food self-sufficiency capacity of a specific region based on biophysical conditions. Recent analyses show that the focus needs to be shifted from foodshed size portrayed as an isotropic circle to a commodity-group-specific spatial configuration of the foodshed that takes into account the socio-economic and biophysical conditions essential to the development of local food supply chains. We focus on a specific animal product (beef) and use an innovative modeling approach based on spatial analysis to detect the areas of the foodshed dedicated to beef feeding (forage, pasture, and grassland), considering the foodshed as a complex of complementary areas called an archipelago. We use available statistical data including a census to address the city-region of Avignon (France) covering a 100 km radius. Our results show that the factors driving the use of short supply chains for beef feeding areas are the foodshed archipelago’s number of patches, the connectivity between them, and the rugosity of the boundaries. In addition, our beef self-sufficiency assessment results differ depending on geographical context. For instance, being located within the perimeters of a nature park seems to help orient beef production towards short supply chains. We discuss possible leverage for public action to reconnect beef production areas to consumption areas (the city) via short supply chains (e.g. green, home-grown school food programs) so as to increase local food security through increased local food self-sufficiency.

Human activities mostly impact the trend and direction of surface water, groundwater, and other river basin resources in the watershed in Africa. Human activities influence river flows and the water quality at both highlands and lowlands. A watershed is indeed a conserved area of land that collects rain and snow and empties or penetrates into ground water sources. The act of managing the activities around the watershed is the Integrated Watershed Management while considering the social, economic, and environmental issues, as well as community interests to manage water resources sustainably. These watersheds, river basins, and groundwater resources provide important services for communities and biodiversity. This paper reveals that the best way to protect groundwater resources is on a watershed basis using IWM. This technique enables us to handle a variety of concerns and objectives while also allowing us to plan in a complicated and uncertain environment. IWM involves cooperation and participation from a wide range of community interests and water users, including municipalities, companies, people, agencies, and landowners, for stakeholders' input to be successful. All of the strategies and plans are produced concerning one another, as well as the overall conditions of the watershed, local land uses, and specific issues.

Consistent calibration and monitoring is a basic prerequisite for providing reliable time series of global and regional sea level variations from altimetry. The precision of sea level measurements and regional biases for six altimeter missions (Jason-1/2/3, Envisat, Saral, Sentinel-3A) is assessed at eleven GNSS-controlled tide gauge stations in the German Bight (SE North Sea) for the period 2002 to 2019. The gauges are partly located at the open water, partly at the coast close to mudflats. The altimetry is extracted at virtual stations with distances from 2 to 24 km from the gauges. The processing is optimized for the region and adjusted for the comparison with instantaneous tide gauges readings. An empirical correction is developed to account for mean height gradients and slight differences of the tidal dynamics between gauge and altimetry which improves the agreement between the two data sets by 15-75%. The precision of the altimeters is depending on location and mission and is shown to be at least 1.8 to 3.7 cm based on an assumed precision of 2 cm for the gauges. The accuracy of the regional mission biases is strongly dependent on the mean sea surface heights near the stations. The most consistent biases are obtained based on the CLS2011 model with mission dependent accuracies from 1.3 to 3.4 cm. Hence, the GNSS-controlled tide gauges operated operationally by WSV might complement the calibration and monitoring activities at dedicated CalVal stations.

Volcano eruptions undoubtly cause environmental impacts and damages. After the eruption, there will be vast barren land that was previously fertile ground covered by vegetation and tree line. Lava from an eruption will flow to the land via a river stream, destroying everything in its path, including vegetation. While the ecosystem actually has an ability to recover. The natural process of ecosystem recovery is related to the succession of vegetation. Then this study aims to assess and model how the ecosystem can recover and how the vegetation can respond to the damage caused by Semeru, one of the most powerful volcanic eruptions on Java island. The study areas were 2 regions that had been impacted by the Semeru lava flow for the period of 2004–2021. Based on the results, the ecosystem recovery of Semeru post-eruption was achieved within 5 years. During this time, the vegetation succession rate, as measured by vegetation cover, increased nearly ten folds. The post-eruption ecosystem recovery was indicated by the ecosystem transformation from a damaged ecosystem indicated by a lava-dominated surface to one with the presence of vegetation and hardened lava. The recovered ecosystem in Semeru's posteruption was composed of solid lava covers (39%), liquid lava (34%), and vegetation covers (27%).Then, the presence of vegetation and its succession rate can be used as a proxy of ecosystem recovery after a vast volcanic eruption.

The combination of organic matter, iron oxide, and clay minerals is of great significance for the adsorption of copper ions (Cu). The purpose of this study is to explore the characteristics of Cu adsorption and laws governing Cu complexation to organic–inorganic, organic–clay mineral, and iron-oxide–clay mineral complexes in the sediments in the estuary of plateau fault and sinking lake——Dianchi Lake. In this study, Cu adsorption tests were performed on the three complexes, in order to study the kinetic behavior of adsorption, Langmuir and Freundlich isotherm models were used. The samples before and after adsorption were characterized via scanning electron microscope (SEM), Fourier infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Our results show that, the Freundlich isotherm models model was able to describe adsorbent behavior in comparison to the Langmuir models. During the Cu adsorption process, the iron-oxide–clay mineral complex is able to adsorb Cu, via coordination exchange, through the –OH contained therein. Organic-matter–clay mineral complexes bonded to the surfaces of clay minerals by replacing the hydroxyl groups with functional groups (carboxyl groups or phenolic hydroxyl groups) contained in the organic matter. Organic–inorganic composites then adsorbed Cu through the coordination exchange of –OH in the polar functional groups of alcohols, phenols, and carboxylic acids. The adsorption capacity of Cu in these three sediment complexes was observed to have the following order: organic–inorganic complex > organic-matter–clay mineral complex > iron-oxide–clay mineral complex. The semi-quantitative analysis results of Fourier Infrared Spectroscopy show that the organic matter (changes in the peak area of functional groups such as carboxyl groups) in the organic-inorganic composite material has an important effect on the amount of copper ions adsorbed by clay minerals.

(1) The article is devoted to the development of a theoretical and algorithmic basis for numerical modeling of the spontaneous potential method (SP) as applied to the study of sandy-argillaceous reservoirs. (2) In terms of coupled flows, we consider a physical-mathematical model of SP signals from an electrochemical source, with regard to the case of fluid-saturated shaly sandstone. (3) An algorithm for 2D finite-element modeling of SP signals was developed and implemented in software, along with its internal and external testing with analytical solutions. The numerical SP modeling was carried out, with determining the dependences on the reservoir thickness and porosity, the amount of argillaceous material and the type of minerals. We performed a comparative analysis of the simulated and field SP data, using the results of laboratory core examinations taken from wells in a number of fields in the Latitudinal Ob Region of Western Siberia. (4) The results of the study may be used either for the development of the existing SP techniques, by providing them with a consistent computational model, or for the design of new experimental approaches.

In this study, we analyzed the feasibility of various carbon neutral methods based on the first principles of biogeochemistry, namely energy use efficiency and elemental stoichiometry. We believe that wood burial is the only currently feasible carbon neutrality method because this method has no theoretical uncertainties, can be implemented immediately, is large scale, low cost, has low technical requirements, and has a relatively low impact on agriculture.

We present here seven new zircon (U-Th)/He (ZHe) ages and three new zircon fission track ages (ZFT) analyzed from an age-elevation profile (Machu Picchu, Peru). ZFT data present older ages in comparison with the other thermochronological data, whereas the ZHe data interestingly present similar ages than the ones obtained with apatite (U-Th)/He (AHe). It has been proposed that He retention in zircon is linked to the damage dose, with an evolution of the closure-temperature from low values associated to low α-dose (<1016 α/g), subsequently increasing before decreasing again at very high α-dose (>1018 α /g). Studies have been focused on the He diffusion behavior at high α-dose, but little is known at low dose. We propose that the ZHe closure temperature at α-dose ranging from 0.6×1015 to 4×1016 α/g is in the range of ~60-80°C. This value is lower than the one proposed in the current damage model ZRDAAM and demonstrates that the ZHe and AHe methods could have similar closure temperatures at low α-dose (i.e. similar ages). These new data strengthen our previous geological conclusions and even highlight an about twice more important cooling rate than the one deduced from AHe and apatite fission-track data alone registered at Machu Picchu.

The efficacy of predicting geochemical parameters with a 2-chain workflow using spectral data as the initial input is evaluated. Spectral measurements spanning the approximate 400-25000nm spectral range are used to train a workflow consisting of a non-negative matrix function (NMF) step, for data reduction, and a random forest regression (RFR) to predict 8 geochemical parameters. Approximately 175000 spectra with their corresponding chemical analysis were available for training, testing and validation purposes. The samples and their spectral and chemical parameters represent 9399 drillcore. Of those, approximately 20000 spectra and their accompanying analysis were used for training and 5000 for model validation. The remaining pairwise data (150000 samples) were used for testing of the method. The data are distributed over 2 large spatial extents (980 km2 and 3025 km2 respectively) and allowed the proposed method to be tested against samples that are spatially distant from the initial training points. Global R2 scores and wt.% RMSE on the 150000 validation samples are Fe(0.95/3.01), SiO2(0.96/3.77), Al2O3(0.92/1.27), TiO(0.68/0.13), CaO(0.89/0.41), MgO(0.87/0.35), K2O(0.65/0.21) and LOI(0.90/1.14), given as Parameter(R2/RMSE), and demonstrate that the proposed method is capable of predicting the 8 parameters and is stable enough, in the environment tested, to extend beyond the training sets initial spatial location.

Atmospheric lightning is an outcome of extreme complex physical processes occurring in the atmosphere. Cloud-to-ground (CG) lightning is considered as a natural disaster. Understanding the importance of CG lightning and implication of the lightning phenomena, Global Climate Observing System (GCOS), world meteorological organization, in its report in the year 2016, introduced the lightning as an Essential Climate Variable (ECV). The present report uses the Lightning Detection Sensor Network (LDSN) established by the National Remote Sensing Centre, Indian Space Research Organization over India to generate the Lightning ECV. A use case of these ECVs are also showcased for an event in Bihar, India, when 42 deaths were reported at locations with large number of CG occurrences.

The contamination of areas around solid urban waste dumps is a global challenge for the maintenance of environmental quality in large urban centres in developing countries. This study applied geophysical methods (electrical resistivity) to identify leachate contamina-tion plumes in the subsoil and groundwater, as well as to describe their temporal (2020 and 2021) dynamics in the lithology and groundwater around the Hulene - B waste dump, Maputo, Mozambique. Geophysical methods (electrical resistivity) were applied to identify possible groundwater contamination plumes, their dynamics, mechanisms of their enrichment and dispersion. Eight 400 m electrical resistivity profiles were performed, four profiles in January 2020 and four profiles in May 2021, overlapped, and the data were inverted with RES2D software. The electrical resistivity models indicate an E - W move-ment of large contamination plumes that dilute superficially into the natural surface wa-ter receiving basin and groundwater, creating zones of resistive anomalies. The thickness of the plumes in the subsurface environment was shown to be extensive in summer for profiles 1a and 2b and we associate it with the higher leachate production and migration mechanisms, which are intense in the hot and rainy season. Profile 4b showed the prop-agation of anomalous surface and subsurface areas, which was associated with higher leachate production and migration process in the new deposition zone (west). The spatial distribution of contamination plumes at both stations reduced significantly as we moved further away from the waste deposit, revealing the attenuating effect of groundwater and lithological substrate (Profile 3 a, b, and fig.7).

Seafood is a nutritious source of protein for billions of people around the world and is generally more sustainable than other animal-based protein sources. As the human population grows, seafood will continue to play an important role in feeding the world. The sustainability of seafood products differs, depending on the species consumed, origin, and production/fishing method. Having access to sustainable seafood products is essential to ensure future generations can continue to consume seafood. We aimed to determine the accessibility of sustainable seafood products to consumers in southeast Queensland, Australia. We surveyed 52,447 fresh, cooked, and processed (packaged) seafood products across southeast Queensland from 2110 establishments (restaurants, supermarket, takeaway shops). We investigated the species, origin and catch method of seafood products and used this information to determine their sustainability according to the Good Fish Guide developed by the Australian Marine Conservation Society. We found enough information to determine the level of sustainability for 36% (n= 18,709) of surveyed products: 4.9% were sustainable, 4.1% were classified as ‘Eat Less’, and 27% were classified as ‘Say No’. The 64% (n=33,737) of products that we could not assess was due to the lack of information at point of sale (16%) or the product was not included in the Good Fish Guide (48%). The top three most accessible sustainable products were Australian farmed barramundi, oysters and prawns. The three most common products to ‘Say No’ were Australian farmed Atlantic salmon, imported prawns and basa. We found that 44% (n= 12,040) of products listed in the Good Fish Guide were lacking origin information. Improving the labelling of species, origin, and catch method of seafood products at the point of sale, especially detailed information about a product’s origin, is essential to improving the accessibility of sustainable seafood.

The unquenchable demand for rock materials has attracted many companies within the building and construction sector to invest in stone quarrying. However, this has brought about the environmental impacts with health threats to people. There is a paucity of information about the magnitude of pollution on air and water and how it varies with quarry sites. This study therefore investigated the physical impacts of quarrying on air and water and explored the in-situ mitigations to undesirable effects due to stone quarrying. Four active quarry sites were identified. Field measurements of dust (particulate matter) was conducted within the four quarry sites and in the nearby community. Water samples were collected from quarry pits and nearby shallow wells for laboratory analysis of water quality. Statistical Analysis of Variance (ANOVA) was used to test for differences in pollution across the four studied sites. Results revealed that, amidst use of wet crushing and water sprinkling on bare surfaces, dust emission was higher than the recommended permissible standards levels with a significant variation across the quarry sites with ANOVA (P-value=0.003) for PM2.5 and (P-value=0.04366) for PM10. Water pollution was mainly contributed by the non-permissive levels of nitrates, chromium, and pH. Polluted air and water are associated with sparking off health threats to the users in the community. In conclusion, quarry companies should strengthen the already existing mitigation of dust suppression. The study recommends additional measures such as treating quarry pit water before discharging to the open environment

While there are extensive studies on the mineralogy and geochemistry of laterites worldwide, the temporal and spatial mineralogical development of a typical nickel laterite profile is still poorly constrained. In this study, we present a detailed mineralogical and geochemical characterization of samples systematically collected from a nickel laterite profile at the Sta. Cruz nickel laterite deposit, Zambales, Philippines, to describe the temporal and spatial development of the laterite profile. Wavelength-dispersive X-ray fluorescence spectroscopy (WDSXRF), mass balance-element mobility calculations, transmitted and reflected light microscopy, and previously reported results from coupled X-ray diffraction (XRD) and Rietveld refinement analyses, reveal that the laterite profile investigated is composed of two main horizons: the limonite and saprolite zones, separated by a thin transitional zone. The main zones are further subdivided into subzones based primarily on the mineral assemblage and major element chemistry: upper limonite, lower limonite, transitional zone, upper saprolite, and lower saprolite. Late-stage garnierite veins were observed cutting the upper and lower saprolite subzones. Investigation of the structure of goethite within the limonite zone via Rietveld refinement show that the crystallinity of goethite decreases with increasing Ni content and increasing crystallite size. This suggests that upwards through the limonite zone, as goethite ages, its crystallinity increases which possibly results in the removal of Ni from its crystal structure and eventual remobilization to the lower laterite zones. We propose a spatio-temporal model of the formation of the Sta. Cruz laterite consisting of four stages: (1) early-stage alteration, (2) continued serpentinization and volume expansion, (3) late stage serpentinization and incipient oxide formation, and (4) goethite ageing and garnierite formation.

Timely crop yield forecasts at national level are substantial to support food policies, to assess agricultural production and to subsidize regions affected by food shortage. This study presents an operational crop yield forecasting system for Poland that employs freely available satellite and agro-meteorological products provided by the Copernicus programme. The crop yield predictors consist of: (1) vegetation condition indicators provided daily by Sentinel-3 OLCI (optical) and SLSTR (thermal) imagery, (2) a backward extension of Sentinel-3 data (before 2018) derived from cross-calibrated MODIS data, (3) air temperature, total precipitation, surface radiation, and soil moisture derived from ERA-5 climate reanalysis generated by the European Centre for Medium-Range Weather Forecasts. The crop yield forecasting algorithm is based on thermal time (growing degree days derived from ERA-5 data) to better follow the crop development stage. The recursive feature elimination is used to derive an optimal set of predictors for each administrative unit, which are ultimately employed by the Extreme Gradient Boosting regressor to forecast yields using official yield statistics as a reference. According to intensive leave-one-year-out cross validation for 2000–2019 period, the relative RMSE for NUTS-2 units are: 8% for winter wheat, and 13% for winter rapeseed and maize. Respectively, for the LAU units it equals 14% for winter wheat, 19% for winter rapeseed, and 27% for maize. The system is designed to be easily applicable in other regions and to be easily adaptable to cloud computing environments (such as DIAS or Amazon AWS), where data sets from the Copernicus programme are directly accessible.

Recently on the December 4, 2021 at 03:00 PM, 3676 m high Mount Semeru located in the East parts of Java Island has erupted. To our best knowledge, an immediate and rapid systematic analysis of the volcanic ash plume courses, PM_2.5 emissions, and environmental impacts based on Mount Semeru eruption has not been implemented so far. Then, this research aims to provide and fill the research gap on the rapid assessment of recent Mount Semeru eruption. From the result, it is clearly visible that for 12 hours the volcanic ash plume course was eastward. The volcanic ash plume can travel a distance of 0–10 km to the North and South directions, and more than 10 km to the East direction. The size of the volcanic ash plume was large at 02:00 AM on December 5, 2021. The smallest size of a volcanic ash plume was recorded at 09:00 PM on December 4, 2021. Most parts of the ash plume (55.98%) or equals 39.01 km² contain fallen volcanic material amounts ranged from 1 kg/m² to 10 kg/m². The fallen volcanic material amount peaked between 08:00 PM and 11:00 PM. Based on the estimation, the PM_2.5 content in the atmosphere increased after the eruption. The mean of PM_2.5 before the eruption was 48.5 ± 19.3(95%CI: 29.2 to 67.8 ug/m³). While after eruption the mean of PM_2.5 was 79.4 ± 32.2(95%CI: 47.2 to112 ug/m³). It indicated that the Mount Semeru eruption has increased the PM_2.5 equals 63.65%.

Forest recreation can be successfully used for the psychological relaxation of respondents and can be used as a remedy for common problems with stress. The special form of forest recreation intended for restoration is forest bathing. These activities might be distracted by some factors, such as viewing buildings in the forest or using a computer in nature, which interrupt psychological relaxation. One factor that might interrupt psychological relaxation is the occurrence of an open dump in the forest during an outdoor experience. To test the hypothesis that an open dump might decrease psychological relaxation, a case study was planned that used a randomized, controlled crossover design. For this purpose, two groups of healthy young adults viewed a control forest or a forest with an open dump in reverse order and filled in psychological questionnaires after each stimulus. A pretest was used. Participants wore oblique eye patches to stop their visual stimulation before the experimental stimulation, and the physical environment was monitored. The results were analyzed using the two-way repeated measures ANOVA. The measured negative psychological indicators significantly increased after viewing the forest with waste, and the five indicators of the Profile of Mood States increased: Tension-Anxiety, Depression-Dejection, Anger-Hostility, Fatigue, and Confusion. In addition, the negative aspect of the Positive and Negative Affect Schedule increased in comparison to the control and pretest. The measured positive indicators significantly decreased after viewing the forest with waste, the positive aspect of the Positive and Negative Affect Schedule decreased, and the Restorative Outcome Scale and Subjective Vitality scores decreased (in comparison to the control and pretest). The occurrence of an open dump in the forest might interrupt a normal restorative experience in the forest by reducing psychological relaxation. Nevertheless, the mechanism of these relevancies is not known, and thus, it will be further investigated. In addition, in a future study, the size of the impact of these open dumps on normal everyday experiences should be investigated. It is proposed that different mechanisms might be responsible for these reactions; however, the aim of this manuscript is to only measure this reaction. The identified psychological reasons for these mechanisms can be assessed in further studies.

The desert locust remains a major threat to global food security. Control operations are a crucial tool to manage crisis; this research investigated the nature of control operations conducted between 2019-2021. Historical data on desert locust and control operations were obtained from the survey reports at the FAO Locust Hub and analysed with respect to survey reports, land cover types, cropland/rangeland extent and crop productivity data. We found that 16.1% of the grid cells with locust presence and 14.9% of the grid cells with control operations had a proportion of rangeland higher than 0.75; while 13.3% of the grid cells with locust presence and 13.2% of the grid cells with control operations had a proportion of croplands higher than 0.75, highlighting that locust presence and control operations were reported in both rangeland and cropland. Control operations continue to be used both to reduce overall locust numbers and to protect crops. Furthermore, through identifying which crops were most at risk, our analyses indicate that wheat production was under the highest strain during periods of increased locust infestations.

The South-to-North Water Transfer Jiangsu Water Supply Area (JWSA) is a mega inter-basin water transfer area (water source) that provides water resources from JiangHuai, combines drainage and flooding management, and regulates nearby rivers and lakes. Analyzing the spatiotemporal soil moisture dynamics in the area will inform agricultural drought and flood disaster assessment and early warning studies. Therefore, we evaluated the quality of European Space Agency Climate Change Initiative Soil moisture (ESA CCI_SM) data in the South-North Water Transfer JWSA. Then, we used ensemble empirical modal decomposition, Mann-Kendall tests, and regression analysis to study the spatiotemporal variation in soil moisture for the past 29 years. The CCI _SM data showed a high correlation with local soil measurements at nine sites. We then analyzed the CCI_SM data from three pumping stations (the Gaogang, Hongze, and Liushan stations) in the South-North Water Transfer JWSA. These stations had similar periodic characteristics of soil moisture, with significant periodic fluctuations around 3.1 d. The overall soil moisture at the three typical pumping stations showed an increasing trend. We then investigated whether there were abrupt soil moisture changes at each station. The spatial distribution of soil moisture in the South-North Water Transfer JWSA was characterized by “dry north and wet south”, with higher soil moisture in winter, followed by autumn, and low soil moisture in spring and summer. Although the linear trend of soil moisture in the South-North Water Transfer JWSA varied in significance, the overall soil moisture in the JWSA has increased over the past 29 years. The areas with significantly enhanced soil moisture are mainly distributed in the Yangzhou and Huai'an areas in the southeastern part of the study area. The areas with significantly decreased soil moisture are small in size and mainly located in northern Xuzhou.

Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments in comparison with the popularly applied machine learning classifiers. This study seeks to explore the feasibility for using a U-Net deep learning architecture to classify bi-temporal high resolution county scale aerial images to determine the spatial extent and changes of land cover classes that directly or indirectly impact tidal marsh. The image set used in the analysis is a collection of a 1-m resolution collection of National Agriculture Imagery Program (NAIP) tiles from 2009 and 2019 covering Beaufort County, South Carolina. The U-net CNN classification results were compared with two machine learning classifiers, the Random Trees (RT) and the Support Vector Machine (SVM). The results revealed a significant accuracy advantage in using the U-Net classifier (92.4%) as opposed to the SVM (81.6%) and RT (75.7%) classifiers for overall accuracy. From the perspective of a GIS analyst or coastal manager, the U-Net classifier is now an easily accessible nad powerful tool for mapping large areas. Change detection analysis indicated little areal change on marsh extent, though increased land development throughout the county has the potential to negatively impact the health of the marshes. Future work should explore applying the constructed U-Net classifier to coastal environments in large geographic areas, while also implementing other data sources (e.g., LIDAR, multispectral data) to enhance classification accuracy.

Cannabis is among the oldest human domesticates and has been subjected to intensive artificial (human-mediated) selection throughout history to create a wide array of varieties and biotypes for diverse uses, including fibre, food, biofuel, medicine and drugs. This paper briefly reviews the available literature on the taxonomy, evolutionary origin and domestication of this plant, as well as its worldwide dispersal, in both its wild and cultivated forms. Emphasis is placed on Europe and especially on the Iberian Peninsula. Today, it is accepted that Cannabis is a monospecific genus with two subspecies, C. sativa subsp. sativa and C. sativa subsp. indica, originating in Europe and Asia, respectively, by allopatric differentiation after geographic isolation fostered by Pleistocene glacial-interglacial cycles. Palynological and phylogeographic evidence situates the Cannabis ancestor on the NE Tibetan Plateau during the mid-Oligocene. The timing and place of domestication is still a matter of debate between contrasting views that defend single or multiple Neolithic domestication centres situated in different parts of the Eurasian supercontinent, notably central/southeastern China and the Caucasus region. Recent meta-analyses have suggested that wild Cannabis may have already been spread across Europe in the Pleistocene, and its domestication could have occurred during the European Copper/Bronze ages. According to the available reviews and meta-analyses, pre-anthropic dispersal of Cannabis into the Iberian Peninsula seems to have occurred only in postglacial times, and the earlier signs of cultivation date to the Early Medieval Ages. However, the palynological and archaeological evidence used to date is insufficient for a sound assessment, and the development of thorough Iberian databases to address further meta-analysis is essential for more robust conclusions. Some clues are provided for these achievements to be fulfilled.

Footprints are powerful indicators for evaluating the impact of the bioeconomy of a country on environmental goods, domestically and abroad. In this study, we apply a hybrid approach combining a Multi-Regional Input-Output model and land use modelling to compute the agricultural land footprint (aLF). Furthermore, we added information on land-use change to the analysis and allocated land conversion to specific commodities. The German case study shows that the aLF abroad is larger by a factor of 2.5 to 3 than the aLF in Germany. In 2005 and 2010, conversion of natural and semi-natural land-cover types abroad allocated to Germany due to import increases was 2.5 times higher than the global average. Import increases to Germany slowed down in 2015 and 2020, reducing land conversion attributed to the German bioeconomy to the global average. The case study shows that the applied land footprint provides clear and meaningful information for policymakers and other stakeholders. The presented methodological approach can be applied to other countries and regions covered in the underlying database EXIOBASE. It can be adapted, also for an assessment of other ecosystem functions, such as water or soil fertility.

The origin of the man at the Earth is directly associated with the determination of directions of the flow distribution of the ancient man migration to adjacent territories. In such studies traditionally mainly landscape and climatological changes are considered. We suggest that along with the above factors, regional tectonic-geodynamic factors played a dominant role in the character of migration. The considered African-Levantine-Caucasian region is one of the most complex regions of the world, where collisional and spreading processes of geodynamics converge. First is determined an essential influence of the Akchagylian hydrospheric maximum (about 200 m above the mean sea level) limiting the ancient men migration from Africa to Eurasia. We propose that the Levantine Corridor emerged after the end of the Akchagylian transgression and landscape forming in the Eastern Mediterranean. This corridor location was formed by the movements between the Dead Sea Transform and the boundary of the carbonate platform of the Mesozoic Terrane Belt. Further landscape evolution was largely determined by the geodynamic behavior of the deep mantle rotating structure occurring below the central part of the region under study. All the mentioned events around and in the Levantine Corridor have been studied in detail on the basis of the combined geodynamic, paleogeographic, and paleomagnetic analyzes performed in northern Israel (Carmel uplift and Galilee plateau). Careful studies of the Evron quarry geological section indicate that it is a unique one for the dating of the marine and continental archaeological sequences and sheds light on the movement of the ancient man along the Levantine Corridor.

The article is devoted to the topical problem of estimating water content in water-oil mixtures and porous media they saturate, according to low-field NMR relaxometry and dielectric spectroscopy. The aim of the research is to theoretically substantiate and experimentally validate the capability of joint interpretation of data from these methods to acquire information on the filtration-volumetric properties of drill cuttings, relaxation characteristics of oil-containing fluids, water/oil ratio in water-oil mixtures and saturated with them drill cuttings in order to control the composition of liquids produced from boreholes. The studies were carried out on samples of cuttings and oils taken from fields in the northern and Arctic regions of the West Siberian oil-and-gas province. Based on the experimental data obtained, we evaluated the water content in the water-oil mixtures, determined the main NMR parameters of the mixtures in terms of properties of the constituent oils, and specified the parameters and shapes of NMR and complex dielectric permittivity spectra. The NMR method was found to be effective in examining high-viscosity and medium-viscosity oils, while the dielectric spectroscopy method – in the study of light oils; their integration allows obtaining reliable data for all the samples under study. We also showed how the shapes of NMR and complex dielectric permittivity spectra depend on the rheological properties of oil belonging to the mixture.

Due to the shortage of agricultural labor forces and rapid aging of farmers, the utilization of tractors is becoming popular and essential in Korea. Tractors can be classified into two types, a walking tractor called as a power tiller and a riding tractor. In this study, agricultural tractors including walking and riding types were categorized into 4 levels by rated output power. And diesel emission inventory of tractors was established and analyzed using 2011 and 2019 survey data in Korea. Emission inventory including CO, NOx, SOx, TSP(PM10), PM2.5, VOCs and NH3 were established using Tier 3 methodology. The total amount of emission using agricultural tractors was decreased about 13% from 2011 to 2019. The number of walking tractors were decreased by about 19% in 8 years, on the other hand that of riding tractors were increased by about 12%. However, the emission reduction is about 48% for walking tractors and the emission increment is about 5% for riding tractors. Thus, the total emission from agricultural tractors was decreased by about 16% in those periods. It is due to the decrease of 21% and 15% in the hours of use of walking and riding tractors, respectively, in 2019. Walking tractors mainly emit air pollutants from spraying and transporting. Riding tractors mainly 61% of total air pollutants emits from soil preparation and transporting operations. Geographic information system (GIS) was used to spatially assign air pollutants variables into 17 provinces and metropolitan cities in Korea. High emission generating regions and changes of emissions during 8 years were clearly seen in GIS analysis. High air pollutant emitting regions are mainly located in the western and southern regions of Korea, which have plenty of arable areas compared to other regions in Korea.

Specific emissivity features of swamps and wetlands of Western Siberia were studied for changing seasonal conditions with the use of daily data of satellite microwave sounding. The research technique involved the analysis of brightness temperatures of the underlying surface at the test sites. Variations in seasonal dynamics of brightness temperatures were mainly caused by different rates of seasonal freezing of the upper waterlogged layer of the underlying surface and dielectric characteristics of water containing natural media (water body, soil, vegetation). We analyzed long-term trends in seasonal and annual dynamics of brightness temperatures of the underlying surface and estimated hydrological changes in the Arctic and Subarctic. The findings open up new possibilities for using satellite data in the microwave range for studying natural seasonal dynamic processes and predicting hazardous hydrological phenomena.

One of the biggest problems that the Dominican Republic has had in recent decades is the efficient management of solid waste produced by the population. This problem has worsened in recent years due to the decrease in available areas for the construction of sanitary landfills, the lack of recycling culture in the population, the deficiency in waste collection, and the scarce legal controls aimed at preserving water and air and soil, among other factors. The objective of this study was to explore the management of solid waste by the population and the municipality of Puñal, province of Santiago, to evaluate and analyze the situation and generation of solid waste, municipal solid waste management services, and the attitudes of the population regarding recycling projects and waste management, to evaluate the viability and sustainability of the use organic waste for energy generation. A total of 275 households from 29 localities in the municipality of Puñal were surveyed, which allowed for a significant population sample. According to the results obtained, the most significant type of waste produced by families is organic waste, followed by plastic waste and paper. Of the total organic waste produced in the municipality, 53% of solid waste is disregarded through the municipal waste collection system, while 47% is used as plant fertilizers or animal feed. On the other hand, most households receive the municipal waste collection service and pay for this service. The results of our research show that the implementation of an energy production system based on organic waste would be viable in the municipality of Puñal. However, a more efficient waste collection system would be necessary and the development of programs and projects that allow all households to participate in the system.

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

Flood Early Warning Systems (FEWSs) using Machine Learning (ML) has gained worldwide popularity. However, determining the most efficient ML technique is still a bottleneck. We assessed FEWSs with three river states, No-alert, Pre-alert, and Alert for flooding, for lead times between 1 to 12 hours using the most common ML techniques, such as Multi-Layer Perceptron (MLP), Logistic Regression (LR), K-Nearest Neighbors (KNN), Naive Bayes (NB), and Random Forest (RF). The Tomebamba catchment in the tropical Andes of Ecuador was selected as case study. For all lead times, MLP models achieve the highest performance followed by LR, with f1-macro (log-loss) scores of 0.82 (0.09) and 0.46 (0.20) for the 1- and 12-hour cases, respectively. The ranking was highly variable for the remaining ML techniques. According to the g-mean, LR models correctly forecast and show more stability at all states, while the MLP models perform better in the Pre-alert and Alert states. Future efforts are recommended to enhance the input data representation and develop communication applications to boost the awareness of the society for floods.

The total lipid and protein content of the invasive caprellid amphipod Caprella scaura, from the biofouling communities of fish farm cages in the Pagasitikos Gulf were analyzed and compared among seasons. Proteins were the most abundant component (48.5 – 49.3%). Lipid content was relatively lower, with a wider range (6.7 – 34%) and showed a distinct seasonal fluctuation with high values in the winter population and a gradual decrease in spring and summer, with the lowest values in Autumn. Composition of the fatty acids profile was consistent among the seasons, with palmitic (16:0), Oleic (18:1n-9), Eicosapentanoic (20:5n-3)(EPA) and Docosahexanoic acid (22:6n-3 )(DHA) being the most abundant fatty acids. The presence of high levels of EPA and DHA fatty acids makes the species a potential candidate for use of these organisms in aquaculture.

Reactive transport (RT) couples bio-geo-chemical reactions and transport. RT is important to understand numerous scientific questions and solve some engineering problems. RT is highly multidisciplinary, which hinders the development of a body of knowledge shared by RT modelers and developers. The goal of this paper is to review the basic conceptual issues shared by all RT problems, so as to facilitate advance along the current frontier: biochemical reactions. To this end, we review the basic equations to point that chemical systems are controlled by the set of equilibrium reactions, which are easy to model, but whose rate is controlled by mixing. Since mixing is not properly represented by the standard advection-dispersion equation (ADE), we conclude that this equation is poor for RT. This leads us to review alternative transport formulations, and the methods to solve RT problems using both the ADE and alternative equations. Since equilibrium is easy, difficulties arise for kinetic reactions, which is especially true for biochemistry, where numerous frontiers are open (how to represent microbial communities, impact of genomics, effect of biofilms on flow and transport, etc.). We conclude with the basic 10 issues that we consider fundamental for any conceptually sound RT effort.

Detailed mapping and structural observations on the Cycladic Blueschist Unit (CBU) of Iraklia island integrated by detrital zircon (DZ) U-Pb ages elucidate the Mesozoic pre-subduction evolution and the Cenozoic orogenic events. Field data reveal that the Iraklia tectonostratigraphy includes a heterogeneous Lower Schist Unit juxtaposed against a Variegated Marble Unit and an overlying Upper Schist Unit. The contact is an extensional ductile-to-brittle-ductile, top-to-N shear zone, associated with the Oligo-Miocene exhumation. The DZ spectrum of the Lower Schist Unit characterized by Gondwanan/peri-Gondwanan provenance signatures points to Late Triassic maximum depositional ages (MDAs). A quartz-rich schist layer yielded Precambrian DZ ages exclusively, considered part of the pre-Variscan metasedimentary Cycladic Basement, equivalent to those observed on Ios island. A significant change occurred during the deposition of the Upper Schist Unit, revealing Late Cretaceous MDAs and a high amount of Late Paleozoic DZ ages, attesting to more internal Pelagonian source areas. The imprint of Paleotethyan vs. Neotethyan geodynamic events is revealed in the DZ U-Pb ages record. The Triassic DZ input demonstrates eroded volcanic material related to the final Paleotethys closure and the Pindos/CBU rift basin opening. Late Cretaceous metamorphic/magmatic zircons and ~48-56 Ma zircon rims constrain the onset of subduction and high-pressure metamorphism.

The movement direction of propagating convective systems originating from both inland and offshore over the north coast of West Java in Indonesia is determined primarily by the prevailing wind. However, the role of a land-sea contrast and a rugged topography over southern West Java is also expected to affect propagating convective systems by increasing land-sea breezes and enhancing upward motion. These hypotheses are tested using a weather prediction model incorporating convection (up to 3 km height) to simulate the heavy rainfall event during 26–29 January associated with the 2002 Jakarta flood. First, we addressed the influence of land-sea contrast and topography on the local circulation, particularly in the area surrounding Jakarta, by replacing the inland topography over western Indonesia (96°–119°E, 17°S–0°) with a water body with an altitude of 0 m. We then compared the results of model simulations with and without topography. The results show that the main role of the topography here is enhancing the upward motion and generating a deep convective cloud in response to the land-based convective system during 26–27 January 2002, which then continuously and rapidly propagates offshore due to the cold pool mechanism. Furthermore, the land-sea contrast has a significant role in increasing sea breeze under the rapidness of the landward propagation system during 28–29 January 2002, which was strengthened by the gravity waves and resulted in early morning convection over coastal regions.

Cannabis is among the oldest human domesticates and has been subjected to intensive artificial (human-mediated) selection through history, to create a wide array of varieties and biotypes for a diversity or uses, including fiber, food, biofuel, medicine and drugs, among others. This paper briefly reviews the available literature on the taxonomy, the evolutionary origin and the domestication of this plant, as well as its worldwide dispersal, either in its wild and cultivated forms. Emphasis is placed on Europe and especially on the Iberian Peninsula, which is the main target of this study. Today it is accepted that Cannabis is a monospecific genus with two subspecies, C. sativa subsp. sativa and C. sativa subsp. indica, originated in Europe and Asia, respectively, by allopatric differentiation after geographical isolation fostered by Pleistocene glacial-interglacial cycles. Palynological and phylogeographical evidence situate the Cannabis ancestor in the NE Tibetan Plateau during the Oligocene (ca. 28 Ma). The timing and place of domestication is still a matter of debate between contrasting views that defend single or multiple domestication centers, situated in different parts of the Eurasian supercontinent, notably central/southeastern China and the Caucasus region. Recent meta-analyses suggest that wild Cannabis may have been spread across Europe already in the Pleistocene (ca. 1 Ma), and its domestication could have been occurred during the European Copper/Bronze ages (7-5 kyr BP). According to the available reviews and meta-analyses, pre-anthropic dispersal of Cannabis into the Iberian Peninsula seems to have been occurred only in post-glacial times (18.5-15 kyr BP) and the earlier signs of cultivation date to the Early Medieval Ages (ca. 600 CE). However, the palynological and archaeological evidence used to date is insufficient for a sound assessment and the development of thorough Iberian databases to address further meta-analysis are essential for more robust conclusions. Some clues are provided for these achievements to be fulfilled.

Radar observation data with high temporal and spatial resolution are used in the data assimilation experiment to improve precipitation forecast of a numerical model. The numerical model considered in this study is Weather Research and Forecasting (WRF) model with double-moment 6-class microphysics scheme (WDM6). We calculated radar equivalent reflectivity factor using higher resolution WRF and compared with radar observations in South Korea. To compare the precipitation forecast characteristics of three-dimensional variational (3D-Var) assimilation of radar data, four experiments are performed based on different precipitation types. Comparisons of the 24-h accumulated rainfall with Automatic Weather Station (AWS) data, Contoured Frequency by Altitude Diagram (CFAD), Time Height Cross Sections (THCS), and vertical hydrometeor profiles are used to evaluate and compare the accuracy. The model simulations are performed with and with-out 3D-VAR radar reflectivity, radial velocity and AWS assimilation for two mesoscale convective cases and two synoptic scale cases. The radar data assimilation experiment improved the location of precipitation area and rainfall intensity compared to the control run. Especially, for the two convective cases, simulating mesoscale convective system was greatly improved.

Tephra plumes can cause a significant hazard for surrounding towns, infrastructure, and air traffic. The current work presents the use of a small and compact X-band Multi-Parameter (X-MP) radar for the remote tephra detection and tracking of two eruptive events at Merapi Volcano, Indonesia, in May and June 2018. Tephra detection was done by analysing the multiple parameters of radar: copolar correlation and reflectivity intensity. These parameters were used to cancel unwanted clutter and retrieve tephra properties, which are grain size and concentration. Real-time spatial and temporal forecasting of tephra dispersal was performed by applying an advection scheme (nowcasting) in the manner of Ensemble Prediction System (EPS). Cross-validation was done using field-survey data, radar observations, and Himawari-8 imagery. The nowcasting model computed both the displacement and growth and decaying rate of the plume based on the temporal changes in two-dimensional movement and tephra concentration, respectively. Our results with ground-based data, where the radar-based estimated grain size distribution fell within the range of in-situ data. The uncertainty of real-time forecasted tephra plume depends on the initial condition, which affects the growth-and decaying rate estimation. The EPS improves the predictability rate by reducing the number of missed and false forecasted events. Our findings and the method presented here are suitable for early warning of tephra fall hazard at the local scale.

The Mediterranean is one of the regions of the world where human-induced climate warming is expected to have large impacts on water and environmental resources. To predict shifts in the current climate system, more regional climate records, including seasonal-to-century scale variability spanning longer than the instrumental periods, are needed. To help fill this gap, we provide a reconstruction of autumn precipitation variations for the Central Pyrenees range since 1500 Common Era (CE) using the varved sediments of Lake Montcortès. To assess the suitability of the calcite sublayer width of the sediments of this lake as a proxy for precipitation anomalies, we performed an analysis and smoothing of the temporal structure of the width series, calibration of the new series with the available instrumental climate records, calculation of a transfer function and testing and comparison of the reconstructed series against available empirical data.The prediction model was statistically robust and showed that the climatic signal was captured in the calcite sublayers. The reconstruction provides the first estimations of regional autumn precipitation shifts in the Central Pyrenees at annual resolution, since 1500 CE. Pronounced interdecadal shifts in precipitation were noticeable; no increasing nor decreasing linear trends or periods of extreme precipitation events were identified. The reconstructed precipitation anomalies suggest a decrease in rainfall during the coldest phase within the coldest period of the Little Ice Age and also during the 20^th century, probably associated to current Global Warming. Correlations between autumn precipitation and the North Atlantic Oscillation, Western Mediterranean Oscillation and Southern Oscillation indices were weak to moderate. A potential relationship with the Atlantic Multidecadal Oscillation pattern is suggested. The reconstructed autumn precipitation trends are coherent with other palaeohydrological reconstructions in similar Mediterranean settings, and consistent at a regional level.

The monitoring of river discharge is vital for the correct management of water resources. A worldwide facility used for measuring discharge are flat-V gauging weirs. These structures consist of a small weir, with a triangular cross-section and a flat “V”-shaped notch. Their extensive use is a consequence of their utility in the measurement of both low and high flow conditions. However, depending on their size, local morphology and river discharge can act as full or partial hydraulic barriers to fish migration. To give answer to this question, the present work studies fish passage performance over flat-V weirs considering their hydraulic performance. For this, radio-tracking and video monitoring observations were combined with computational fluid dynamics (CFD) models in two flat-V weirs, using Iberian barbel (Luciobarbus bocagei) as target species. Results show that fish passage is conditioned by both hydraulic and behavioral processes, providing evidences about the scenarios where flat-V weirs may act as full or partial barriers to upstream movements. For the studied flat-V weirs, a discharge range of 0.27-8 m3/s, with a water drop difference between upstream and downstream water levels lower than 0.7 m and a depth downstream the weir higher than 0.30 m can be considered as an effective passage situation for barbels. These findings are of interest to quantify flat-V weir impacts, for engineering applications and to establish managing or retrofitting actions when required.

In response to the COVID-19 pandemic, and resultant cancellation of geoscience fieldwork, as well as outstanding accessibility issues inherent in conducting fieldwork, we developed a virtual geological fieldtrip (VFT) to the Huronian age deposits in the Whitefish Falls area, Ontario, Canada. This region is a geologically significant site in which many Ontario universities conduct undergraduate teaching due to the high-quality exposures. In this contribution we describe and comment on the development of this openly available resource, the motivations in doing so, the challenges faced, its pedagogical impact and relevance, as well as provide suggestions to others in the development of such resources. Our multimedia VFT combines 360° imagery, georeferenced data on integrated maps, and multi-scale imagery (aerial/drone, outcrop, and thin section images). The VFT was built using the Esri Storymaps platform, and thus offers us the opportunity to review the effectiveness of building such resources using this medium, as well as our approach to doing so. We conclude that the Esri Storymaps platform provides a sound medium for the dissemination of multimedia VFTs, but that some aspects of in-person fieldwork remain hard to replicate. Most notably, ‘hands on experience’ and specific activities such as geological mapping. In addition, while VFTs alleviate some accessibility barriers to geoscience fieldwork, substantial barriers remain that should remain the focus of both pedagogical and geoscience work.

The presented results of simulations take into account the optical parameters of the selected sea region (from literature data on the southern Baltic Sea) and two optically extreme types of crude oil (from historical data) which exist in the form of a highly diluted oil-in-water emulsion (10 ppm). The spectral index was analyzed based on the results of modelling the radiance reflectance distribution for almost an entire hemisphere of the sky (zenith angle from 0 to 80o). The spectral index was selected and is universal for all optically different types of oil (wavelengths 650 and 412 nm). The possibility of detecting pollution in the conditions of the wavy sea surface (as a result of wind of up to 10 m/s) was studied. It has been also shown that if the viewing direction is close to a direction perpendicular to the sea surface, observations aimed at determining the spectral index are less effective than observation under the zenith angle of incidence of sunlight for all azimuths excluding the direction of sunlight specular reflection.

In unicellular organisms, intracellular inclusions of amorphous calcium carbonate (ACC) have been initially described in cyanobacteria and, later, in unicellular eukaryotes of Lake Geneva (Switzerland/France). Inclusions in unicellular eukaryotes ‒named micropearls‒ consist of hydrated ACCs, frequently enriched in Sr or Ba, displaying internal oscillatory zonations due to variations in the Ba:Ca or Sr:Ca ratios. The analysis of our database consisting of 1597 micropearl analyses from Lake Geneva and 34 from Lake Titicaca (Bolivia/Peru) has shown that a certain number of Sr and Ba-enriched micropearls from these lakes contain As in amounts measurable by EDXS. A Q-mode statistical analysis has confirmed the existence of five geochemically distinct morpho-chemical groups of As-bearing micropearls, among which a new category identified in Lake Geneva, where As is often associated with Mg. This new type of micropearl is possibly produced in a small (7-12 m size) bi-flagellated organism. Micropearls from Lake Titicaca, which contain Sr, are found in an organism very similar to Tetraselmis cordiformis, observed in Lake Geneva. Lake Titicaca micropearls contain higher As concentrations which can be explained by the high As concentration in the water of this lake. The ubiquity of the biomineralization process observed points to the need for better understanding of the role of amorphous or crystalline calcium carbonates in As cycling in surface waters.

Having experienced large-scale disasters between 2004 and 2006, the fatalities due to large-scale disasters in 2018 were still high. In contrast, disaster risk management (DRM) and CDR in Japan have been continuously improved. Thus, there is a need to develop CDR for supporting DRM in Indonesia by learning from the Japanese experience, particularly in a disaster-prone area without large-scale disaster experience. This research was a pilot project on the development of CDR in Indonesia. The case study was a geological hazard-prone Lembang Fault area. People’s perception was collected using structured interviews, while demographic and local economic data was acquired from official statistical publications. Satellite imageries were utilized to acquire natural and built environment and land use/land cover and their changes between 2019 and 2021. Although the degrees of social capital, risk knowledge including indigenous knowledge and past disaster experience were high, government interventions on DRM and land administration are required to develop CDR in Lembang Fault area. Organized community development is expected rather than to solely involve NGOs. Moreover, strategies to develop economic resilience are needed to allow the community to bounce back from future disaster. Finally, a detail baseline data should be collected to develop DRM strategy and CDR.

The work consisted in identifying possible effects from heavy metals (HMs) pollution due to waste disposal activities in three potentially polluted sites located in Basilicata (Italy), where a release of pollutants with values over the thresholds allowed by the Italian legislation was detected. The potential variations in the physiological efficiency of vegetation have been analyzed through the multitemporal processing of satellite images. In detail, Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) images were used to calculate the Normalized Difference Vegetation Index (NDVI) trend over the years. Then, the multitemporal trends were analyzed using the median of Theil-Sen, a non-parametric estimator particularly suitable for the treatment of remote sensing data, being able to minimize the outlier effects due to exogenous factors. Finally, the subsequent application of the Mann-Kendall test on the trends identified by Theil-Sen slope allowed the evaluation of trends significance and, therefore, the areas characterized by the effects of contamination on vegetation. The application of the procedure to the three survey sites led to the exclusion of the presence of significant effects of HMs contamination on the vegetation surrounding the sites during the years of waste disposal activities.

We simulate the effects of diagenesis, cementation and compaction on the elastic properties of shales and sandstones with four different petro-elastical theories and a basin-evolution model, based on constant heating and sedimentation rates. We consider shales composed of clay minerals, mainly smectite and illite, depending on the burial depth, and the pore space is assumed to be saturated with water at hydrostatic conditions. Diagenesis in shale (smectite/illite transformation here) as a function of depth is described by a 5th-order kinetic equation, based on an Arrhenius reaction rate. On the other hand, quartz cementation in sandstones is based on a model that estimates the volume of precipitated quartz cement and the resulting porosity loss from the temperature history, using an equation relating the precipitation rate to temperature. Effective pressure effects (additional compaction) are accounted for by using Athy equation and the Hertz-Mindlin model. The petro-elastic models yield similar seismic velocities, despite the different level of complexity and physics approaches, with increasing density and seismic velocities as a function of depth. The methodology provides a simple procedure to obtain the velocity of shales and sandstones versus temperature and pressure due to the diagenesis-cementation-compaction process.

The research was conducted in the Kırklareli stream, which flows southwest through the city of the same name toward the village of Kavaklı. The aim of the study is to evaluate water analysis results and assess the potential that the European Union drinking water standard for lead can be achieved in the Kırklareli stream by reliance on the low solubility of lead phosphate minerals. The present study used Visual MINTEQ 3.1 for all water chemistry simulations. The European Union drinking water standard for lead, which is 10 μg L⁻¹, is exceeded at least once and as many as three times at seven of the ten sites during the 2018 sampling season. Although the database solubility of hydroxypyromorphite is exceeded in most samples, it appears this may be the result of major ion substitutions in the hydroxypromorphite that forms in the Kırklareli stream which increases the effective solubility of lead in the stream.

This study aims to evaluate the land surface temperature (LST) and the thermal characteristics of the Urban Canopy Layer (UCL) of the urban canyon in Avenida Rio Branco in the Central Business District (CBD) of Rio de Janeiro during summer. In order to conduct this evaluation, two methods were employed: 1) TIRS Landsat-8 sensor for data selection and processing (latest generation, 2011-2020); ; 2) field survey using nine sampling points — seven along two mobile transects, one fixed point, and one vertical measurement point, which required the use of a RPA (Remotely Piloted Aircraft). Three categories of analysis were established for the field survey based on the prevailing synoptic situations: stability, instability, and post-instability. The CBD is characterized by extensive areas with surface heat islands, in which temperatures were higher than 38.9°C; the areas with milder LSTs were Campo do Santana, Avenida Rio Branco, and one of the Mixed-Use Zones (Praça Mauá). With respect to Rio Branco Avenue, the LST niches of lowest elevation were derived through building shadowing; however, the orbital data diverged from the observation data of the ten field-study days. In situ data revealed that the characteristics urban morphology of Avenida Rio Branco is susceptible to the formation of heat islands, presenting heat islands of very strong magnitude (over 6.1°C) in atmospheric stability, strong magnitude (4.1-6.0°C) in atmospheric instability, and moderate magnitude (2.1°C-4.0°C) in post-atmospheric instability. Despite the synoptic situation, thermal cores were concentrated at 1 pm. The intersection between Avenida Rio Branco, Rua do Ouvidor, and Praça Mauá stored most of the solar energy received during the day due to the greater sky obstruction caused by the verticalization. Finally, vertical analysis demonstrated the formation of a thermal inversion on the night of the highest mean air temperature (29.5°C), probably, due to the roughness and number of buildings in the urban canyon.

How robust is our assessment of impacts to ecosystems and species from a rapidly changing climate during the 21st century? We examine the challenges of uncertainty, complexity and constraints associated with applying climate projections to understanding future biological responses. This includes an evaluation of how to incorporate the uncertainty associated with different greenhouse gas emissions scenarios and climate models, and constraints of spatiotemporal scales and resolution of climate data into impact assessments. We describe the challenges of identifying relevant climate metrics for ecological models and evaluate the usefulness and limitations of different methodologies of applying climate change to both quantitative and qualitative ecological response models. We discuss the importance of incorporating extreme climate events and their stochastic tendencies in assessing ecological impacts and transformation, and provide recommendations for better integration of complex climate-ecological interactions at relevant spatiotemporal scales. We further recognize the compounding nature of uncertainty when accounting for our limited understanding of the interactions between climate and biological processes. Given the inherent complexity in ecological processes and their interactions with climate, we recommend integrating quantitative modeling with expert elicitation from diverse disciplines and experiential understanding of recent climate-driven ecological processes to develop more robust understanding of ecological responses under different scenarios of future climate change. Inherently complex interactions between climate and biological systems also provide an opportunity to develop wide-ranging strategies that resource managers can employ to prepare for the future.

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement was supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often characterized by an underlying climate gradient, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated variability. To solve this limitation, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial patern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern. Both calibrations reached comparable performance of Q. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

Current satellite remote sensing methods struggle to detect and map forest degradation, a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrain, despite the fact that much of the worlds’ remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising the level of multilooking in the interferometric processing chain strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available.

The desert locust remains a major threat to global food security. Control operations are a crucial tool to manage crisis; this research investigated the nature of control operations conducted between 2019-2021. Historical data on desert locust and control operations were obtained from the survey reports at the FAO Locust Hub and analysed with respect to survey reports, land cover types, cropland/rangeland extent and crop productivity data. We found that 16.1% of the grid cells with locust presence and 14.9% of the grid cells with control operations had a proportion of rangeland higher than 0.75; while 13.3% of the grid cells with locust presence and 13.2% of the grid cells with control operations had a proportion of croplands higher than 0.75, highlighting that locust presence and control operations were reported in both rangeland and cropland. Control operations continue to be used both to reduce overall locust numbers and to protect crops. Furthermore, through identifying which crops were most at risk, our analyses indicate that wheat production was under the highest strain during periods of increased locust infestations.

Seyfe Lake is an important part of the natural ecosystem of Central Anatolia and lies within a 1487 km² closed basin. Groundwater withdrawal for irrigation and recent climatic change have caused lake area to decrease for decades and to completely disappear briefly in August 2008. Groundwater quality is crucial for sustainable irrigation in the Seyfe Basin. A key finding of this study is the difference in the Hardie-Eugster alkalinity-to-calcium ratio of the lake water and that of most groundwater wells in the basin. This difference in the chemical signature of Seyfe Lake and basin groundwater means the evaporative salinization pathway of most groundwater discharged into the lake cannot account for the composition of Seyfe Lake. The ratio of actual evapotranspiration to precipitation will increase under current climate change projections. A second finding, with implications for soil salinization, is that most groundwater in Seyfe Basin has a Hardie-Eugster alkalinity-tocalcium ratio greater than unity, meaning soil alkalization will accompany soil salinization.

The distributed acoustic sensing (DAS) has great potential for monitoring natural-resource reservoirs and borehole conditions. However, the large volume of data and complicated wavefield add challenges to processing and interpretation. In this study, we demonstrate that seismic interferometry based on deconvolution is a convenient tool for analyzing this complicated wavefield. We extract coherent wave from the observation of a borehole DAS system at the Brady geothermal field in Nevada. Then, we analyze the coherent reverberating waves, which are used for monitoring temporal changes of the system. These reverberations are tirelessly observed in the vertical borehole DAS data due to cable or casing ringing. The deconvolution method allows us to examine the wavefield at different boundary conditions. We interpret the deconvolved wavefields using a simple 1D string model. The velocity of this wave varies with depth, observation time, temperature, and pressure. We find the velocity is sensitive to disturbances in the borehole related to increasing operation intensity. The velocity decreases with rising temperature, which potentially suggests that the DAS cable or the casing are subjected to high temperature. This reverberation can be decomposed into distinct vibration modes in the spectrum. We find that the wave is dispersive, and the the fundamental mode propagate with a large velocity. The method can be useful for monitoring borehole conditions or reservoir property changes. For the later, we need better coupling than through only friction in the vertical borehole to obtain coherent energy from the formation.

Abstract: Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereas the rainfall effect on the increasingly dry conditions was more subtle than annual and seasonal declines and greater annual variation, which warrants further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action.

Three significant changes have occurred in the winter climate in Europe recently: increased UK flooding; Iberian drought; and warmer temperatures north of the Alps. The literature links all three to a persistent, significant increase in sea level pressure over Southern Europe, the Medi-terranean, Iberia and the Eastern Atlantic (SEMIEA) which changes the atmospheric circulation system: forcing cold fronts to the north away from Iberia; and creating a south westerly flow around the northern perimeter of the high-pressure region bringing warmer, moist air from the subtropical Atlantic to the UK and Europe which increases precipitation in the UK and raises the temperature in Europe. I use the Last Millennium Ensemble, MERRA-2 and Terra-NCEP data to demonstrate that the extreme, anthropogenic, West African aerosol Plume (WAP) which only exists from December to April perturbs the northern, regional Hadley Circulation creating the high pressure in the SEMIEA. I also show that the anthropogenic WAP has only existed in its extreme form in recent decades as the two major sources of the WAP aerosols: biomass burning; and gas flaring have both increased significantly since 1950 due to: a four-fold increase in population; and gas flaring rising from zero to 7.4 billion m3/annum and note that this time span coincides with the changes in the three elements of the winter climate of Europe. I also suggest that it may be possible to eliminate the WAP and return the winter climate of Europe to its natural state after the crucial first step of recognising the cause of the changes is taken.

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n=82), and feedback on the draft report was obtained from a focus group (n=5). User requirements were assessed and validated using a post-campaign survey (n=31). The UCD research was conducted amongst participants in Ljubljana, Slovenia and the results report was distributed among the participating cities across Europe. The feedback received made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution.

The term deviation frequency denotes the boundary between the variable part of the amplitude and phase scintillation spectrum and the part of uninformative noises. We suggested the concept of the “characteristic deviation frequency” during the observation period which is defined as the most probable value of the deviation frequency under current local conditions. This work is a case study of the characteristic deviation frequency (fd) registered for GPS, GLONASS, Galileo and SBAS signals under quiet and weakly disturbed geomagnetic conditions in April 2021 at the mid-latitude GNSS station. Our results demonstrated that the fd value for all signal components of GPS, GLONASS and GALILEO signals varied within 15-22 Hz. The characteristic deviation frequency was 20 Hz for the mentioned GNSS signals. In difference, the deviation frequency was limited within 13-20 Hz for SBAS with the lower characteristic deviation frequency at 18 Hz. We assume that the concept of the characteristic deviation frequency can be used to determine the optimal sampling rate of the GNSS carrier phase data for the ionospheric studies. The characteristic deviation frequency can also characterize the state of the regular trans-ionospheric radio channel.

Coastal urbanisation is a widespread phenomenon throughout the world and is often linked to increased erosion. Small Pacific islands are not spared from this issue, which is of great importance in the context of climate change. The French Polynesian island of Bora Bora was used as a case study to investigate the historical evolution of its coastline classification and position from 1955 to 2019. A time series of very-high-resolution aerial imagery was processed to highlight the changes of the island’s coastline. The overall length of natural shores, including beaches, decreased by 46% from 1955 to 2019 while man-made shores such as seawalls increased by 476%, and as of 2019 represented 61% of the coastline. This evolution alters sedimentary processes: the time series of aerial images highlights increased erosion in the vicinity of seawalls and embankments, leading to the incremental need to construct additional walls. In addition, the gradual removal of natural shoreline types modifies landscapes and may negatively impact marine biodiversity. Through documenting coastal changes on Bora Bora through time, this study highlights the impacts of man-made structures on erosional processes and underscores the need for sustainable coastal management plans in French Polynesia.

Electric streamer discharges (streamers) in air are a very important stage of lightning, taking place before formation of the leader discharge, and with which an electric discharge starts from conducting objects which enhance the background elecric field, such as airplanes. Despite years of research, it is still not well understood what mechanism determines the values of streamer parameters, such as its radius and propagation velocity. The Streamer Parameter Model (SPM) is aimed to understand this mechanism, as well as to provide a way to efficiently calculate streamer parameters. Previously, we demonstrated that SPM results compared well with a limited set of experimental data. In this Brief Report, we compare SPM predictions to the published hydrodynamic simulation (HDS) results.

The Sanshui Basin (SSB) is located at the northern continental margin of the South China Sea and characterized by a continental rift basin. The bimodal volcanic rocks in SSB record the early Cenozoic magmatic activity in the South China Block, on the magmatic evolution process of bimodal volcanic rocks are poorly understood. Clinopyroxenes in bimodal volcanic rocks in the SSB provide an opportunity to investigate the magma process during magma ascent. We classified nine types of clinopyroxene phenocrysts according to the different compositions and textures types in cogenetic basalt-trachyandesite-comenditic trachyte, the composition of unzoned clinopyroxene have an evolution sequence of diopside- hedenbergite- aegirine with the decrease of Mg#, and the trace element contents of unzoned clinopyroxenes also increase systematically during magma evolution, indicating that the genesis of clinopyroxene dominated by fractional crystallization in a closed magma system; however, the clinopyroxenes with reverse zoning and multiple zoning record the process of magma mixing and recharge indicating an open magma system. Whilst fractional crystallization is the dominated process, magma mixing, recharge, and crystal settling complicate magma evolution. Thermobarometric calculations show that clinopyroxene phenocrysts in bimodal volcanic rocks of SSB are distributed in the whole crust during magma ascent. We have established a magma plumbing system, which provides a new constrain for the complex magmatic evolution history in the SSB by detailed mineral-scale analysis.

Many corporations and governments aspire to become Net Zero Carbon Dioxide by 2030-2050. Achieving this goal requires understanding where energy is produced and consumed, the magnitude of CO₂ generation, and the Carbon Cycle. Many prior proposed solutions focus on reducing future CO₂ emissions from continued use of fossil fuels. Examination of these technologies exposes their limitations and shows that none offer a complete solution. For example, bioethanol is shown to be both carbon and energy inefficient. Direct Air Capture technologies are needed to reduce CO₂ already in the air. The most natural form of Direct Air Capture involves letting nature do the work of creating biomass via photosynthesis. However, it is necessary to break the Carbon Cycle by permanently sequestering that biomass carbon in “landfills” modified to discourage decomposition to CO₂ and methane. Tree leaves and biomass grown on-purpose, such as high yield switchgrass, are proposed as good biomass sources for this purpose. Left unsequestered, leaves decompose with a short Carbon Cycle time constant releasing CO₂ back to the atmosphere. While in any given year, leaves represent a small fraction of a tree’s above ground biomass, leaves can represent a substantial fraction of the total biomass generated by a tree when integrated over a tree’s lifetime. Understanding the chemistry of the distinct phases landfills undergo is the key to minimizing or eliminating decomposition. First, the compact cross-linked structure of cellulose and keeping water out will make it difficult for initial depolymerization to release sugars. Air ingress should be minimized to minimize Phase I aerobic decomposition. pH manipulation can discourage acid formation during Phase II. Lignocellulose is low in nutrients needed for anaerobic decomposition. Inhibitors can be added if needed. The goal is to move quickly to the dormant phase where decomposition stops. The cost for Carbon Capture and Storage (CCS) for growing and sequestering high yield switchgrass is estimated to be lower than CCS for steam reforming of methane hydrogen plants (SRM) and supercritical or combined cycle coal power plants. Thus, sequestration of biomass is a natural, carbon efficient, and low-cost method of Direct Capture. Biomass sequestration can provide CO₂ removal on giga tonnes per year scale and can be implemented in the needed timeframe (2030-2050).

Aquaponics are efficient systems that associate aquatic organisms’ production and plants by recirculating water and nutrients between aquaculture and hydroponic tanks. In this study, we have characterised the bacterial communities in the fresh water aquaponics system that can mineralise polysaccharides and phytate by producing carbohydrate degrading enzymes and phytases, by 16S rRNA gene sequencing and in vitro culture techniques. Around 20% of the operational taxonomic units (OTUs) identified were previously reported to carry fibre-degrading enzymes putative genes, namely β-glucanase (1%), xylanase (5%) or cellulases (17%). Ten % of the OTUs were previously reported to carry putative genes of phytases with different catalytic mechanisms, namely β-propeller (6%), histidine acid phytases (3%) and protein tyrosine phytase (&lt;1%). Thirty-eight morphologically different bacteria were isolated from biofilms accumulated in fish and plant compartments, and identified to belong to the Bacilli class. Among these, seven could produce xylanase, 8 produced β-glucanase, 14 produced cellulase, and 11 isolates could secrete amylases. In addition, Staphylococcus sp. and Rossellomorea sp. could produce consistent extracellular phytate-degrading activity. The PCR amplification of β-propeller genes both in environmental samples and in the isolates obtained showed that this is the most ecologically relevant phytase type in the aquaponics systems used. In summary, the aquaponics system is abundant with bacteria carrying enzymes responsible for plant-nutrient mineralisation.

Urban air quality is increasingly being studied as a fraction of the world's population is now living in megacities. In this study, particulate matter (PM) along Taft Avenue, Manila, Philippines, is investigated in terms of its ability to induce genetic damage on human peripheral blood lymphocytes (PBL). Size-segregated roadside air samples were obtained from 2015-2016 near the university gate and analyzed using in vitro micronucleus and cytokinesis-block proliferation tests. While cellular proliferation was unaffected by 0 – 0.1 kg·m-3 of PM1.0 and PM2.5, PBL cells treated with PM2.5 displayed significantly higher micronucleus count (p = 0.03) compared to the cells treated with PM1.0. Atomic Absorption Spectroscopy revealed greater amounts of Cd, Ca, Pb, K, Na, and Zn in PM2.5 compared to PM1.0. The results indicate the differences in composition of the two size fractions of air particulates are associated with their genotoxicities.

Agriculture in Morocco has been extensive until the middle of the 20th century due to the distribution of rainfall and the availability of water. In the middle of the last century hydraulic works were built that allowed the transition to intensive agriculture by the increase of irrigated areas, allowing that in the territories where there is water for irrigation and the climate allows it, the crops adapt to the demands of the market. The objective of the study is to assess by satellite images the land cover between 1985 and 2020, analyzing the changes in cultivation areas, as well as the changes in desert, sub-desert and forest areas of the Oum Er Rbia hydrological basin in Morocco. Landsat satellite images have been used since 1984 by the US government (Aerospace and Geological Agencies). A series of vegetation indices (NDVI, RVI, TNDVI and EVI) have been used; among which TNDVI (Transformed Normalized Vegetation Index) stands out for its better accuracy, which has allowed us to distinguish vegetation in cultivated and forest areas, as well as arid zones. In addition, the study has compared the use of two methodologies to calculate changes in the coverage of the Earth’s surface, has used local image processing from the Sentinel Application Platform tool and has also used the Google Earth Engine tool. The latter being the most optimal, although at the moment it has great limitations. In both methodologies and in the different indices it has been possible to observe during these 35 years as the cultivated area has increased (related to the availability of water by the construction of reservoirs and canals), how plant cover has improved in forest areas, and a range of variations in arid areas.

This study examines the effect of surface currents on the bulk algorithm calculation of wind stress estimated using the scatterometer data during 2007-2020 in the Indian Ocean. In the study region as a whole the wind stress decreased by 5.4% by including currents into the wind stress equation. The most significant reduction in the wind stress is found along the most energetic regions with strong currents such as Somali Current, Equatorial Jets and Aghulhas retroflection. A highest reduction of 11.5% is observed along the equator where the Equatorial Jets prevail. A sensitivity analysis has been carried out for the study region and for different seasons to assess the relative impact of winds and currents in the estimation of wind stress by changing the winds while keeping the currents constants and vice versa. The inclusion of currents decreased the wind stress and this decrease is prominent when the currents are stronger. This study showed that equatorial Indian Ocean is the most sensitive region where the current can impact on wind stress estimation. The results showed that uncertainties in the wind stress estimations are quite large at regional levels and hence better representation of wind stress incorporating ocean currents should be considered in the ocean/climatic models for accurate air-sea interaction studies.

The Life Cycle Analysis (LCA) was used to assess the impact of biomethane plant of the “La Católica” in Pedregal-Majes-Arequipa farm, fed with cow manure and holding a production of 60 Nm3/day of purified biogas. Life cycle inventory, impact assessment and interpretation were performed. The functional unit established was 1 MJ of energy produced; the study was modeled with SimaPro software, Ecoinvent Database and ReCiPe Midpoint (H) impact assessment methodology, according to the impact categories of climate change and fossil resource depletion. The impact analysis was limited to the Well to Tank (WTT) approach, which involves feedstock transport, substrate mixed, anaerobic digestion, biogas purification, storage and injection of the fuel into transport vehicles. The digestion process generated the highest amount of CO2 emissions (1.79E-02 kg CO2 eq/MJ-biomethane) and the highest depletion of fossil resources (6.58E-03 kg oil eq/MJ-biomethane), compared to the other fuel production, due to energy consumption and transport infrastructure. Biomethane was then compared to fossil fuels, resulting in natural gas generating the least amount of CO2 emissions, followed by diesel and finally biomethane. For the fossil resource depletion category, biomethane presented the lowest amount of fossil fuel consumption (1.37E-02 kg oil eq/MJ-biomethane), followed by natural gas and diesel.

This study presents the results of a research project financed by the Lazio Regional Government. The research focused on defining an integrated model of recent alluvial deposits in the Tiber River. To achieve this objective, geological boreholes were made to monitor the aquifer and in situ and laboratory tests carried out. The data obtained was used to detail stratigraphic aspects and improve the comprehension of water circulation beneath the recent alluvial deposits of the Tiber River in the urban area of Rome, between the Ponte Milvio bridge and the Tiber Island. The stratigraphic intervals recognised in the boreholes were parameterised based on their litho-technical characteristics. The new data acquired, and integrated with existing data in the CNR IGAG database, made it possible to produce a three-dimensional model of the lithologies in the study area.The model of the subsoil, simplified for applied reasons, was described in hy-drostratigraphic terms: three different lithotypes were subjected to piezometric levels monitor-ing. Finally, the research generated a numerical hydrological level in a stationary regime. In general, this study demonstrates how a numerical hydrogeological model calibrated by piezo-metric monitoring data can support the construction of a geological model, discarding or con-firming certain hypotheses and suggesting other means of reconstructing sedimentary bodies.

Physical processes play important roles in controlling eutrophication and oligotrophication. In stratified lakes, internal waves can cause vertical transport of heat and nutrients without breaking the stratification, through boundary mixing events. Such is the case in tropical Valle de Bravo (VB) lake, where strong diurnal winds drive internal waves, boundary mixing and hypolimnetic warming during stratification periods. We monitored VB during 18 years (2001-2018) when important water-level fluctuations (WLF) occurred, affecting mixing and nutrient flux. Mean hypolimnetic temperature increase (0.06–1.04°C month-1) occurred in all the stratifications monitored. We analyzed temperature distributions and modeled the hypolimnion heat budget to assess vertical mixing between layers (26,618–140,526 m-3h-1), vertical diffusivity coefficient KZ (6.2x10-7–3.3x10-6 m2s-1) and vertical nutrient entrainment to epilimnion on monthly scale. Stability also varied as a function of WLF. Nutrient flux to the epilimnion ranged 0.36–5.99 mg m-2d-1 for soluble reactive phosphorus (SRP) and 5.8–97.1 mg m-2d-1 for dissolved inorganic nitrogen (DIN). During low water-level years, vertical nutrient fluxes increase and can account for up to &gt;40% of the total external nutrients load to the lake. Vertical mixing changes related to WLF affect nutrient recycling, their flux to sediments, ecosystemic metabolic balance and planktonic composition of VB.

Lightning has received a lot of attention in scientific literature during the recent decade, not only because it is an impressive atmospheric phenomenon but also its associations with severe storms that cause unprecedented damages to agriculture, electric power networks, property, and life. This study assessed the Spatio-temporal characteristics of lightning occurrence with elevation in Uganda using lightning flash and elevation datasets for a period of fifteen years (1998-2013). Datasets used in this study included daily lightning flashes as captured by Lightning Imaging Sensor (LIS) aboard on Tropical Rainfall Measurement Mission (TRMM) satellite and elevation data in form of Digital Elevation Model (DEM) obtained from the Shuttle Radar Topography Mission (SRTM). Spatio-temporal results indicated that ~80% of areas with an elevation that ranges from 800-1200 m above mean sea level (masl) in Uganda had severe lightning occurrences and ~20% of areas with an elevation greater than 1200 m (masl) had severe lightning occurrences. The country received an enhanced number of lighting events with the highest number in 1999. Subsequently, a reduced trend was observed from 2002 to 2007 followed by an increment in the number of lightning events in (2010, 2011, 2012, and 2013). The intensity of the events decreased gradually though two peaks were observed, (1998-2001) and (2010-2013). Furthermore, results indicate escalations in the frequency and duration of lightning events from 60 times in 1998 to approximately 200 times in 2013 and from 1000 microseconds in 1998 to more than 2000 microseconds in 2013. Generally, the country experienced an enhanced increase in lighting occurrences over the study period which therefore calls for urgent actions to combat the root cause and also provide effective measures to reduce the impacts of lightning strikes.

The influence of the Madden - Julian Oscillation (MJO) on the intensity of the Tropical Cyclones in the North Indian Ocean is investigated through a machine learning algorithm using cyclone data from the Joint Typhoon Warning Centre and MJO from the Bureau of Meteorology, Australia during 1974–2019. The scatter index varies from 0.45 for depressions to 0.03 for the super cyclonic storms indicating that the MJO index is another parameter that should be investigated in cyclone studies.

In Korea, rice is a major staple grain and is mainly cultivated using various agricultural machinery. Air pollutants emitted from agricultural machinery have their origins mainly from the exhaustion of internal combustion engines. In this study, emission characteristics of five main air pollutants by European Environment Agency's Tier 1 method for rice cultivation was analyzed. Diesel is a main fuel for agricultural machinery and gasoline is generally used only for rice transplanters as a fuel in Korea. Tractors consume 46% of total fuel consumption and 56% of diesel fuel consumption. Gasoline used for rice transplanters accounts for 17% of total fuel consumption each year. Tractors and rice transplanters are emitting 82% of all total pollutants. From 2011 to 2019, the total amount of air pollutant emissions was decrease by 15%. That accounted for the reduction of rice cultivation fields in those periods. Rice transplanting operation was in charge of 42% of total emissions. Then, harrowing, harvesting, tilling, leveling, and pest control operations generated 10%, 10%, 8%, 8% and 7% of total emissions, respectively. The contribution of each air pollutant held 54% of CO, 39% of NOx, 5% of NMVOC, and 2% of TSP from the total emission inventory. The three major regions emitting air pollutants from mechanized agricultural practices were Jeollanam-do, Chungcheongnam-do, and Jeollabuk-do, which consume 55% of total fuel usage in rice farming. The total amount of air pollutant emissions from rice cultivation practices in 2019 was calculated as 8,448 Mg in Korea.

Nature-based solutions (NbS) —i.e. working with and enhancing nature to address societal challenges— feature with increasing prominence in responses to climate change, including in the adaptation plans of the most vulnerable nations. Although evidence for the effectiveness of NbS for adaptation is growing, there is less evidence on whether and how NbS reduce vulnerability to climate change in the Global South, despite this region being home to most of the world’s most climate-vulnerable people. To address this, we analysed the vulnerability-reduction outcomes of 85 nature-based interventions in rural areas across the Global South, and factors mediating their effectiveness, based on a systematic map of peer-reviewed studies encompassing a wide diversity of ecosystems, climate impacts, intervention types and institutions. We applied an analytical framework based on social-ecological systems and climate change vulnerability, coding studies with respect to six pathways of vulnerability reduction: social and ecological exposure, sensitivity, and adaptive capacity. We find widespread effectiveness of NbS in the dataset with 95% providing positive outcomes for climate change adaptation. Overall, nature-based interventions reduced vulnerability primarily by lowering ecosystem sensitivity to climate impacts (73% of interventions), followed by reducing social sensitivity (43%), reducing ecological exposure (37%), and/or increasing social adaptive capacity (34%), ecological adaptive capacity (18%) and reducing social exposure (12%). With an analysis of mediating factors, we show that vulnerability-reduction effectiveness was affected as much by social and political factors as by technical considerations. Indeed configurations of existing and introduced formal and informal institutions appear central to the efficacy and distributive effects of the studied interventions. We conclude that attention to the distinct pathways through which vulnerability is reduced can help maximise the benefits of NbS and that to be successful, careful consideration is required on their applicability to particular circumstances as well as their social dimensions.

Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

The water quality of the river is becoming deteriorated due to human interference. It is essential to understand the relationship between human activities and land-use types to assess the water quality of a region. GIS has the latest tool for analyzing the spatial correlation. Land use land cover and change detection is the best illustration to show the human interactions on land features. The study assessed water quality index of upper Ganga River near Haridwar, Uttarakhand and spatially correlated them with changing land use to reach a logical conclusion. At the upper course of Ganga along 78 Km long from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index the physicochemical parameters like pH, EC, DO, TDS, CaCO3-, CaCO3, Cl¯, Ca++, Mg++, Na+, K+, F-, Fe2+ were considered. The result of the spatial analysis was evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index of selected sampling sites was estimated as 0.1443. The spatial correlation between land-use change and site-wise differences in water quality index has also shown a high positive correlation with R² = 0.8455. The degree of positive correlation and root mean square error has strongly indicated that the water quality of the river at the upper course of Ganga is highly impacted through human activities.

The planetary boundary layer height (PBLH) is one of the key factors in influencing the dispersion of the air pollutants in the troposphere and hence the air pollutant concentration on ground level. For this reason, accurate air pollutant concentration depends on the performance of PBLH prediction. Recently, ceilometer, a lidar instrument to measure cloud base height, has been used by atmospheric scientists and air pollution control authorities to determine the mixing level height (MLH) in improving forecasting and understanding the evolution of aerosol layers above ground at a site. In this study, ceilometer data at an urban (Lidcombe) and a rural (Merriwa) location in the New South Wales, Australia was used to validate the PBLH prediction from two air quality models (CCAM-CTM and WRF-CMAQ) as well as to understand the aerosol transport from sources to receptor point at Merriwa for the three case studies where high PM10 concentration was detected in each of the three days. The results show that the PBLH prediction by the two air quality models corresponds reasonably well with observed ceilometer data and the cause and source of high PM10 concentration at Merriwa can be found by using ceilometer MLH data to corroborate with back trajectory analysis of transport of aerosols to the receptor point at Merriwa. Of the three case studies, one had aerosol source from north and north west of Merriwa in remote NSW where windblown dust is the main source, and the other two had sources from south and south east of Merriwa where anthropogenic sources dominate,

It is widely accepted that plastic waste is one of our most urgent environmental concerns the world is currently facing. Plastic has contributed greatly to innovation in all fields, but the raw material for its production (fossil fuels), as well as the linear economy in which it is currently produced and used, makes the material problematic from a sustainability and human health perspectives. The emergence of bio-based plastics provides an opportunity to reduce dependency on fossil fuels and transition to a more circular plastics economy. For polyethylene terephthalate (PET), one of the most prevalent plastics in packaging and textiles, there exist two bio-based alternatives that are similar or superior in material property and recyclability. These are polyethylene furanoate (PEF) and polytrimethylene terephthalate (PTT). The overarching aim of this study was to examine the transition from fossil-based to renewable plastics, through the lens of PET upcycling into PEF and PTT. The process for the production of PEF and PTT from three feed streams (post-consumer PET waste, lignocellulosic biomass-derived cellulose and biodiesel-derived crude glycerol) was developed in the software SuperPro Designer and the economic viability assessed via a discounted cumulative cash flow (DCCF) analysis. This study represents a conceptual case study of the valorisation of existing plastic waste into new, recyclable bio-based plastics, for a more sustainable plastics production. A techno-economic analysis of the designed process revealed that the minimum selling price (MSP) of second generation-derived PEF and PTT is 3.13 USD/kg, and that utilities and the feedstock used for the production of 2,5-furandicarboxylic acid (FDCA) needed in PEF synthesis contributed the most to the process operating costs. The effect of recycling PEF and PTT through the process at three recycling rates (42%, 50% and 55%) was investigated and revealed that increased recycling could reduce the MSP of the 2G bio-plastics (by 48.5%) to 1.61 USD/kg. This demonstrates that increasing recycling rates would have a beneficial effect on the economic viability of the plastic biorefinery.

Background: Residents of a large area of North-Eastern Italy were exposed for decades to high concentrations of perfluoroalkyl and polyfluoroalkyl substances (PFAS) via drinking water. Despite the large amount of evidence in adults of a positive association between serum PFAS and metabolic outcomes, studies focusing on children and adolescents are limited. We evaluated the associations between serum PFAS concentrations and lipid profile, blood pressure and body mass index (BMI) in highly exposed adolescents and children. Methods: A cross-sectional analysis was conducted in 6669 adolescents (14-19 years) and 2693 children (8-11 years) enrolled in the health surveillance program of the Veneto Region. Non-fasting blood samples were obtained and analyzed for perfluorooctanoic acid (PFOA) perfluorooctane sulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorononanoic acid (PFNA), total cholesterol (TC) high-density lipoprotein cholesterol (HDL-C) and triglycerides. Low-density lipoprotein cholesterol (LDL-C) was calculated. Systolic and diastolic blood pressure (BP) were measured and BMI z-score accounting for age and sex was estimated. The associations between ln-transformed PFAS (and categorized into quartiles) and continuous outcomes were assessed using generalized additive models. Analyses were stratified by gender and adjusted for potential confounders. Results: Among adolescents, significant associations were detected between all investigated PFAS and TC, LDL-C, and to a fewer extent HDL-C. Among children, PFOS and PFNA had significant associations with TC, LDL-C and HDL-C, while PFOA and PFHxS had significant associations with HDL-C only. Increased serum concentrations of PFAS, particularly PFOS, were associated with decreased BMI z-score. No statistically significant associations were observed between PFAS concentrations and BP. Conclusions: Our study supports a consistent association between PFAS concentration and serum lipids, stronger for PFOS and PFNA and with a greater magnitude among children compared to adolescents, and a negative association of PFAS with BMI.

With this article, impact of effluent mixed water with the quality of the Mansagar Lake has been established by evaluating the physico-chemical parameters and the heavy-metal contents experimentally. The process of calculating water quality and the metal pollution quality indices is also explained in brief with respect to selected sample locations and varied environmental conditions (Pre- and Post-Monsoon season). Distribution trends of Pearson‘s correlation factor have also been discussed to establish their relation among the physico-chemical parameters and the heavy-metal contents for varied environmental conditions. In the end, detailed discussion on observations made during this study and useful recommendations are also elaborated in details. With this article, we intend to present a document for better understanding of the water quality of this lake in view of futuristic management strategies to be adopted to maintain it heritage values.

Climate change is a major threat to agricultural food production globally and locally. It poses both direct and indirect effects on soil functions. Thus, agricultural management practices has evolved to adaptation strategies in order to mitigate the risks and threats from climate change. The study concludes with a recommendation the coconut farmers should explore the idea of soil biodiversity in a bid to mitigate the potential negative impact of climate related risk on the farming. The study proffers the need for adopting sustainable agricultural practices to boost local coconut production. This can contribute to the simultaneous realisation of two of the Sustainable Development Goals (SDGs) of the United Nations: SDG 2 on food security and sustainable agriculture and SDG 13 on action to combat climate change and its impacts. The study findings has implications for tackling climate change in Sub-Saharan Africa and in particular Nigeria in order to boost local agricultural production and coconut in particular without negative environmental consequences and an ability to cope with climate change related risks.

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

The Mediterranean basin is a hot spot of climate change where the Posidonia oceanica (L.) Delile (PO) and other seagrass are under stress due to its effect on marine habitats and the rising influence of anthropogenic activities (tourism, fishery). The PO and seabed ecosystems, in the coastal environments of Pantelleria and Lampedusa, suffer additional growing impacts from tourism in synergy with specific stress factors due to increasing vessel traffic for supplying potable water, fossil fuels for electrical power generation. Earth Observation (EO) data, provided by high resolution (HR) multi/hyperspectral operative satellite sensors of the last generation (i.e. Sentinel 2 MSI and PRISMA) have been successfully tested, using innovative calibration and sea truth collecting methods, for monitoring and mapping of PO meadows under stress, in the coastal waters of these islands, located in the Sicily Channel, to better support the sustainable management of these vulnerable ecosystems. The area of interest in Pantelleria was where the first prototype of the Italian Inertial Sea Wave Energy Converter (ISWEC) for renewable energy production was installed in 2015, and sea truth campaigns on the PO meadows were conducted. The PO of Lampedusa coastal areas, impacted by ship traffic linked to the previous factors and tropicalization effects of Italy southernmost climate change transitional zone, was mapped through a multi/hyper spectral EO-based approach, using training/testing data provided by side scan sonar data, previously acquired. Some advanced machine learning algorithms (MLA) were successfully evaluated with different supervised regression/classification models to map seabed and PO meadow classes and related Leaf Area Index (LAI) distributions in the areas of interest, using multi/hyperspectral data atmospherically corrected via different advanced approaches.

The present review is dedicated to using of peat on the example of fen peat in high added-value products and applications. Mainly, but not limited, last decade literature was analysed from the perspective of innovation potential of peat applications in environmental technologies on examples of studies from the Baltic Sea region. Paper covers a wide range of applications of peat products started from agriculture to medicine and cosmetics. A separate chapter is devoted to the deep-processed peat product - humic substances (humate, humic and fulvic salts and acids). Generalised dependence of product extraction rate and its properties, depending on the process parameters are provided. Widely are described applications of the humic sub-stance applications covering economic aspects, such as production costs. In the last chapter of the review are given recommendations for applications considering the most recent trends of peat-based product developments. This accumulated information could be useful for future production, development of new, environmentally friendly products and start-ups establishment.

Assuming that climate warming in the WSL will lead to a northward shift of the forest and permafrost boundaries, a “substituting space for time” approach predicts an increase in concentration of DIC and labile major and trace elements and a decrease of the transport of DOC and low soluble trace metals in the form of colloids in the main stem of the Ob River. However, an unknown factor is the change in hydrochemistry of the largest southern tributary, the Irtysh River, which is impacted by permafrost-free steppe and forest-steppe zone. Overall, seasonally-resolved transect studies of large riverine systems of western Siberia are needed to assess the hydrochemical response of this environmentally-important territory to on-going climate change.

Mangrove vegetation plays a vital role in habitat and nursing ground for different organisms and prevents coastal erosion caused by wave and tide action. In recent years the mangrove vegetation in Chattogram coast, Bangladesh, has been interrupted by other infrastructural development, which has a destructing effect on the surrounding environment. Land surface temperature analysis of an area helps learn about different environmental conditions, weather, and climate. It is also essential to monitor the rising temperature and global warming, the biggest threat to humanity. NDBI and NDVI are the efficient process for monitoring vegetation and build up areas of a geographical location. This study focused on those analyses to understand the importance of mangrove vegetation in the Salimpur area and surrounding coastal areas of Chattogram by studying the relationship between NDVI and NDBI, NDVI and LST, NDBI, and LST. The outcome indicates that a higher vegetation index results in lower land surface temperature during different periods, negatively correlated. This study also found a strong positive correlation between buildup index (NDBI) and land surface temperature (LST), which means Land Surface temperature was found higher in Buildup areas. The vegetation areas are greatly affected by the buildup areas. The correlation between buildup areas and vegetation areas was strongly negative, which means an increase of NDBI decreases NDVI, and a decrease of NDBI increases NDVI.

The aim of this paper is to apply a new lane separation methodology for the maritime sector emissions attributed to the different vessel types and marine traffic loads in the Mediterranean and the Black Sea defined via the European Marine and Observation Data network (EMODnet), developed in 2016. This methodology is implemented for the first time on the Copernicus Atmospheric Monitoring Service Global Shipping (CAMS-GLOB-SHIP v2.1) nitrogen dioxide (NOX) emissions inventory, on the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) tropospheric vertical column densities and on the LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) chemical transport model simulations. By applying this new, EMODnet-based lane separation method to the CAMS-GLOB-SHIP v2.1 emission inventory, we find that cargo and tanker vessels account for approximately 80% of the total emissions in the Mediterranean, followed by fishing, passenger, and other vessel emissions with contributions of 8%, 7% and 5%, respectively. Tropospheric NO2 vertical column densities sensed by TROPOMI for 2019 and simulated by the LOTOS-EUROS CTM have been successfully attributed to the major vessel activities in the Mediterranean; the mean annual NO2 load of the observations and the simulations reported for the entire maritime EMODnet-reported fleet of the Mediterranean is in satisfactory agreement, 1.26 ± 0.56x1015 molecules cm-2 and 0.98 ± 0.41x1015 molecules cm-2, respectively. The spatial correlation of the annual maritime NO2 loads of all vessel types between observation and simulation ranges between 0.93 and 0.98. On seasonal basis, both observations and simulations show a common variability. The winter-time comparisons are in excellent agreement for the highest emitting sector, cargo vessels, with the observations reporting a mean load of 0.98 ± 0.54 and the simulations of 0.81 ± 0.45x1015 molecules cm-2 and correlation of 0.88. Similarly, the passenger sector reports 0.45 ± 0.49 and 0.39 ± 0.45x1015 molecules cm-2 respectively, with correlation of 0.95. In summertime, the simulations report a higher decrease in modelled tropospheric columns than the observations, however still resulting in a high correlation between 0.85 and 0.94 for all sectors. These encouraging findings will permit us to proceed with creating a top-down inventory for NOx shipping emissions using S5P/TROPOMI satellite observations and a data assimilation technique based on the LOTOS-EUROS chemical transport model.

Globally, saline lakes occupying 23% by area 44% by volume among all the lakes might desiccate by 2025 due to agricultural diversion, illegal encroachment, pollution, and invasive species. India’s largest saline lake, Sambhar is currently shrinking at the rate of 4.23% due to illegal saltpan en-croachment. This research article aims to identify the trend of migratory birds and monthly wetland status. Birds survey was conducted for 2019, 2020 and 2021 and combined with literature data of 1994, 2003, and 2013 for visiting trend, feeding habit, migratory and resident ratio, and ecological diversity index analysis. Normalized Difference Water Index was scripted in Google Earth Engine. Results state that it has been suitable for 97 species. Highest NDWI values for the was whole study period was 0.71 in 2021 and lowest 0.008 in 2019 which is highly fluctuating. The decreasing trend of migratory birds coupled with decreasing water level indicates the dubious status for its existence. If the causal factors are not checked, it might completely desiccate by 2059 as per its future prediction. Certain steps are suggested that might help conservation. Least, the cost of restoration might exceed the revenue generation.

The topic of this paper is the airborne evaluation of ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) measurement capabilities and surface-height-determination over crevassed glacial terrain, with a focus on the geodetical accuracy of geophysical data collected from a helicopter. To obtain surface heights over crevassed and otherwise complex ice surface, ICESat-2 data are analyzed using the density-dimension algorithm for ice surfaces (DDA-ice), which yields surface heights at the nominal 0.7~m along-track spacing of ATLAS data. As the result of an ongoing surge, Negribreen, Svalbard, provided an ideal situation for the validation objectives in 2018 and 2019, because many different crevasse types and morphologically complex ice surfaces existed in close proximity. Airborne geophysical data, including laser altimeter data (profilometer data at 905~nm frequency), differential Global Positioning System (GPS), Inertial Measurement Unit (IMU) data, on-board-time-lapse imagery and photographs, were collected during two campaigns in summers of 2018 and 2019. Airborne experiment setup, geodetical correction and data processing steps are described here. To date, there is relatively little knowledge of the geodetical accuracy that can be obtained from kinematic data collection from a helicopter. Our study finds that (1)~Kinematic GPS data collection with correction in post-processing yields higher accuracies than Real-Time-Kinematic (RTK) data collection. (2)~Processing of only the rover data using the Natural Resources Canada Spatial Reference System Precise Point Positioning (CSRS-PPP) software is sufficiently accurate for the sub-satellite validation purpose. (3)~Distances between ICESat-2 ground tracks and airborne ground tracks were generally better than 25~m, while distance between predicted and actual ICESat-2 ground track was on the order of 9~m, which allows direct comparison of ice-surface heights and spatial statistical characteristics of crevasses from the satellite and airborne measurements. (4)~The Lasertech Universal Laser System (ULS), operated at up to 300~m above ground level, yields full return frequency (400~Hz) and 0.06-0.08~m on-ice along-track spacing of height measurements. (5)~Cross-over differences of airborne laser altimeter data are 0.1918 $\pm$ 2.385~m along straight paths over generally crevassed terrain, which implies a precision of approximately 2.4~m for ICESat-2 validation experiments. (6)~In summary, the comparatively light-weight experiment setup of a suite of small survey equipment mounted on a Eurocopter (Helicopter AS-350) and kinematic GPS data analyzed in post-processing using CSRS-PPP leads to high accuracy repeats of the ICESat-2 tracks. The technical results (1)-(6) indicate that direct comparison of ice-surface heights and crevasse depths from the ICESat-2 and airborne laser altimeter data is warranted. The final result of the validation is that ICESat-2 ATLAS data, analyzed with the DDA-ice, facilitate surface-height determination over crevassed terrain, in good agreement with airborne data, including spatial characteristics, such as surface roughness, crevasse spacing and depth, which are key informants on the deformation and dynamics of a glacier during surge.

The use of convolutional neural networks (CNNs) in image classification has become the standard method of approaching computer vision problems. Here we apply pre-trained networks to classify images of non-breaking, plunging and spilling breaking waves. The CNNs are used as basic feature extractors and a classifier is then trained on top of these networks. The dynamic nature of breaking waves is exploited by using image sequences to gain extra information and improve the classification results. We also see improved classification performance in using pre-computed image features such as the optical flow between image pairs. The inclusion of the dynamic information improves the classification between breaking wave classes. We also provide corrections to the methodology from the article from which the data originates to achieve a more accurate assessment of performance.

Main purposes and research question: Wheat is the second largest grain crop by tonnage in the world and the largest in Denmark. Given the observed, adverse impacts on wheat yields of climate change and the importance of wheat in the human diet, the purpose of this study was to use life cycle assessment to compare conventional wheat farming with indoor vertical farming using hydroponics. Methods: Life Cycle Assessment was used to assess the base case systems up to the “farm gate” for 1 tonne of wheat grain. The processes contributing most of the impacts were identified, and scenarios were assessed to determine how much the impacts could be reduced. Results: The conventional system outperformed the base case vertical system in every impact category, due to the electricity consumption in the lighting system. The scenarios included increasing the efficiency of the LED lighting and using 100% wind energy, but the conventional system still outperformed the vertical system by significant margins in all impact categories. This was due to the low photosynthetic conversion efficiency and the high energy density of wheat. Conclusions: Until significant improvements are made to lighting efficiency, the photosynthesis conversion efficiency of wheat, new wheat variants designed for vertical gardens and the sustainability of electricity supply, conventional wheat production will be environmentally preferable and vertical gardens would be advised to focus on food products with low energy densities.

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

Cumulative effects of landscape disturbance in forested source water regions can alter the storage of fine sediment and associated phosphorus in riverbeds, shift nutrient dynamics and degrade water quality. Here, we examine longitudinal changes in major element chemistry and particulate phosphorus (PP) fractions of river-bed sediment in an oligotrophic river during environmentally sensitive low flow conditions. Study sites along 50 km of the Crowsnest River were located below tributary inflows from sub-watersheds and represent a gradient of increasing cumulative sedi-ment pressures across a range of land disturbance types (harvesting, wildfire, and municipal wastewater discharges). Major elements (Si2O, Al2O3, Fe2O3, MnO, CaO, MgO, Na2O, K2O, Ti2O, V2O5, P2O5), loss on ignition (LOI), PP fractions (NH4CI-RP, BD-RP, NaOH-RP, HCI-RP and NaOH(85)-RP) and absolute particle size were evaluated for sediments collected in 2016 and 2017. While total PP concentrations were similar across all sites, bioavailable PP fractions (BD-RP, NaOH-RP) increased downstream with increased concentrations of Al2O3 and MnO and levels of landscape disturbance. This study highlights the longitudinal water quality impacts of increasing landscape disturbance on bioavailable PP in fine riverbed sediments and shows how the convergence of climate (wildfire) and anthropogenic (sewage effluent, harvesting, agriculture) drivers can produce legacy effects on nutrients.

The topic of this paper is the airborne evaluation of ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) measurement capabilities and surface-height-determination over crevassed glacial terrain, with a focus on the geodetical accuracy of geophysical data collected from a helicopter. To obtain surface heights over crevassed and otherwise complex ice surface, ICESat-2 data are analyzed using the density-dimension algorithm for ice surfaces (DDA-ice), which yields surface heights at the nominal 0.7~m along-track spacing of ATLAS data. As the result of an ongoing surge, Negribreen, Svalbard, provided an ideal situation for the validation objectives in 2018 and 2019, because many different crevasse types and morphologically complex ice surfaces existed in close proximity. Airborne geophysical data, including laser altimeter data (profilometer data at 905~nm frequency), differential Global Positioning System (GPS), Inertial Measurement Unit (IMU) data, on-board-time-lapse imagery and photographs, were collected during two campaigns in summers of 2018 and 2019. Airborne experiment setup, geodetical correction and data processing steps are described here. To date, there is relatively little knowledge of the geodetical accuracy that can be obtained from kinematic data collection from a helicopter. Our study finds that (1)~Kinematic GPS data collection with correction in post-processing yields higher accuracies than Real-Time-Kinematic (RTK) data collection. (2)~Processing of only the rover data using the Natural Resources Canada Spatial Reference System Precise Point Positioning (CSRS-PPP) software is sufficiently accurate for the sub-satellite validation purpose. (3)~Distances between ICESat-2 ground tracks and airborne ground tracks were generally better than 25~m, while distance between predicted and actual ICESat-2 ground track was on the order of 9~m, which allows direct comparison of ice-surface heights and spatial statistical characteristics of crevasses from the satellite and airborne measurements. (4)~The Lasertech Universal Laser System (ULS), operated at up to 300~m above ground level, yields full return frequency (400~Hz) and 0.06-0.08~m on-ice along-track spacing of height measurements. (5)~Cross-over differences of airborne laser altimeter data are 0.1918 $\pm$ 2.385~m along straight paths over generally crevassed terrain, which implies a precision of approximately 2.4~m for ICESat-2 validation experiments. (6)~In summary, the comparatively light-weight experiment setup of a suite of small survey equipment mounted on a Eurocopter (Helicopter AS-350) and kinematic GPS data analyzed in post-processing using CSRS-PPP leads to high accuracy repeats of the ICESat-2 tracks. The technical results (1)-(6) indicate that direct comparison of ice-surface heights and crevasse depths from the ICESat-2 and airborne laser altimeter data is warranted. The final result of the validation is that ICESat-2 ATLAS data, analyzed with the DDA-ice, facilitate surface-height determination over crevassed terrain, in good agreement with airborne data, including spatial characteristics, such as surface roughness, crevasse spacing and depth, which are key informants on the deformation and dynamics of a glacier during surge.