Sediment plumes, released to the Bering Sea from the delta front of the Yukon River, Alaska, are initiated mainly by glacier-melt sediment runoffs in the glacierized regions of the Yukon River drainage basin. The surface sediment plumes are extended around the fan-shaped Yukon River delta, which is followed by the northwestward dispersion. During continuous measure-ments of the Yukon River discharge and sediment load, behaviors of the sediment plumes were explored by shipboard observations in the Bering Sea offshore from the Yukon delta. At the high river sediment load of ca. 3000 kg/s, the plume partially plunged into the sea bottom layer. The plunging probably originated in the nepheloid-layer formation from the flocculation of river-suspended sediment, of which more than 90 %wt. is silt and clay (grain size d < 0.063 mm). In order to numerically obtain the area of the surface sediment plumes, a satellite image analy-sis was performed by using three near-infrared bands in MODIS/Aqua or MODIS/Terra. The plume area was significantly correlated (R2=0.735, p<0.01) to the sediment load averaged for the two days with time lags of 20 days and 21 days to the date of a certain satellite image. Hence, the dispersion of plume-suspended sediment appears to be controlled by the sediment runoff events in the Yukon River rather than the northward “Alaskan Coastal Water”.

Remote sensing/GIS techniques are a versatile tool for x-raying serial forest structural changes in retrospect. It would be impossible to evaluate past occurrences and changes in forest extents in past decades at Effan Forest Reserve without non-conventional means. Therefore, we adopted remote sensing technology using Landsat images to evaluate land-use change and degradation rates in the area with a view to ascertaining causal factors for possible minimization of forest degradation in Effan Forest Reserve. Land-use/land-cover changes were analyzed using USGS-Landsat TM and ETM images of 1987, 2002, 2014 and 2019. Field-data were collected using handheld GPS receiver and spatial statistical analyses were conducted using the ground control points (GCPs). For inventory data, a systematic sampling technique was adopted using ten 1.05 km-transects at 500 m intervals. A total of 50 sample plots of 50 × 50 m were used. All tree species with Dbh ≥10 cm were enumerated. Nineteen tree species in ten families were encountered with Vitellaria paradoxa as the most-frequently occurring species in the area. IUCN-listed endangered Pterocarpus erinaceus, hitherto abundant in the area, was rarely encountered during the survey, while Vitellaria paradoxa is gradually shrinking, going the relative abundance in the area. The result further showed that primary and secondary forests decreased considerably by 258.03 ha (46.72%) and 9.18 ha (3.63%), respectively, with a total forest loss of 50.3% in 32 years (8.4 hayr-1, 1.6% per annum). While forest plantation size doubled by 369.72 ha within the period. This is worrisome as the remaining fragmented forests appeared to be on the decline, except the riparian vegetation, due to inaccessibility to the riparian by loggers. It thus appeared that forest protection approaches were ineffective. Increased protection efforts could save this forest reserve, and the concerned authority should consider a focused-enrichment planting involving indigenous species for ecosystem-repair.

While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to the experience of consciousness: “what is it like being a stakeholder?”. Such experience will help to break free of established norms in science and political processes.

Deep learning classification is the state-of-the-art of machine learning approach. Earlier work proves that the deep convolutional neural network has successfully and brilliantly in different applications such as images or video data. Recognizing and clarifying the remote sensing aspect of the earth's surface and exploit land cover and land use (LCLU). First, this article summarized the remote sensing emerging application and challenges for deep learning methods. Second, we propose four approaches to learn efficient and effective CNNs to transfer image representation on the ImageNet dataset to recognize LCLU datasets. We use VGG16, Inception-ResNet-V2, Inception-V3, and DenseNet201 models to extract features from the EACC dataset. We use pre-trained CNNs on ImageNet to extract features. For feature selection we proposed principal component analysis (PCA) to improve accuracy and speed up the model. We train our model by multi-layer perceptron (MLP) as a classifier. Lastly, we apply the multi-granularity encoding ensemble model. We achieve an overall accuracy of 92.3% for the nine-class classification problem. This work will help remote sensing scientists understand deep learning tools and apply them in large-scale remote sensing challenges

The Katangese Copperbelt area (KCA) located south-eastern of D.R. Congo presents high concentration of metal trace elements (MTE) in several soils due to a rich natural geochemical background, and intense mining activities, causing serious health issues to humans and animals. However, the lack of data on specific baseline concentrations makes it difficult to properly assess and monitor the environmental quality of soils in the region. In this study, the baseline concentration of 11 potentially toxic MTE (i.e., Mn, Zn, Cu, Co, Cr, Pb, Cd, Ti, Ni, Al, and Fe) was assessed in topsoils of the KCA, and the possible influence of land uses (croplands, forest and mining areas) was examined. Results showed the following baseline concentrations, i.e. lower and upper limits (mg.kg^-1) in cropland soils : Al (18.4–162.0), Cd (0.0–0.1), Co (0.1–3.5), Cu (0.8–17.7), Cr (0.0–0.2), Fe (4.7–233.8), Mn (3.5–575.6), Ni (0.1–1.9), Pb (0.2–2.4), Zn (0.1–20.3), Ti (0.0–392.6); in forests: Al (18.8–1167.1), Cd (0.02–0.48), Co (0.20–18.1), Cu (3.6–42.7), Cr (0.1–33.7), Fe (86.4–283.3), Mn (4.9–1538.9), Ni (0.05–24.2), Pb (0.3–13.7), Zn (2.0–7.0), Ti (0.2–0.8); and in mining areas: Al (7.4–241.2), Cd (0.01–164.8), Co (0.2–211.3), Cu (2.4–5485.4), Cr (0.03–0.4), Fe (5.9–481.6), Mn (7.1–95.9), Ni (0.1–1.9), Pb (0.2–390.8), Zn (1.5–5629.3), Ti (0.1–1.3). Cu and Zn were highest in mining areas demonstrating a prevalent influence of mining activities in altering the natural background of metals concentrations in the region. By contrast, croplands and forest shared a similar trend of Al and Mn contents, suggesting a mild influence of agricultural activity. Intriguingly, higher Cu and Co contents were found in forest compared to croplands. For all the three studied land uses, no straightforward relation was found between metal concentrations and soil total acidity. This study is the first attempt to establish reference values of MTE contents in the KCA soils and thus provides valuable information for legislative purposes and for soil quality assessment.

An Environmental Decision Support System (EDSS) can be used as an important tool for rehabilitation and preservation of ecosystems. Nonetheless, high assimilation costs (both money and time) are one of the main reasons that these tools are not widely adapted in practice. This work presents a low-cost paradigm of "EDSS as a Service", this paradigm is demonstrated for developing Water Quality EDSS as a Service that utilizes the well-known CE-QUAL-W2 model as a kernel for deriving optimized decisions. The paradigm is leveraging new open-source technologies in software development (e.g. Docker, Kubernetes, and Helm) with cloud computing in order to significantly reduce assimilation costs of the EDSS for organizations and researchers working on rehabilitation and preservation of water bodies.

Oil palm is one of the most important crops in Malaysia. Lately, the production of oil palm has been reduced due to a variety of factors, including the weather and climate. Temperature, wind speed, relative humidity, sunshine, and rainfall distribution all have an impact on palm tree growth and development, which in turn has an impact on oil palm production. This paper aims to investigate the effects of some weather elements (temperature, wind speed, relative humidity, sunshine, and rainfall) on oil palm production in Peninsular Malaysia. Data were analyzed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, and multiple linear regression (MLR). The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature, sunshine, wind speed, relative humidity, and rainfall (independent variables). The findings revealed that temperature, wind speed, relative humidity, sunshine, and rainfall have a low impact on oil palm production and yield turnover. The R2 value of 0.202 shows that the independent variables explained only 20.2% of the fluctuation in palm oil production. The study recommends working within an integrated approach involving scientific research, planting, improving variety, improving regional academic leadership, and engaging private and public stakeholders, emphasized collaborative efforts with researchers in consumer countries, and strengthening the capacity of growers to best agroecological practices.

The aim of this research is to expand recent developments in the mapping of pasture yield with remotely piloted aircraft systems to that of satellite-borne imagery. Up to date, spatially explicit and accurate information of the pasture resource base is needed for improved climate-adapted livestock rangeland grazing. This study developed deep learning predictive models of pasture yield, as total standing dry matter in tonnes per hectare (TSDM(tha−1)), from field measurements and both remotely piloted aircraft systems and satellite imagery. Repeated remotely piloted aircraft system structure measurements derived from structure from motion photogrammetry, provided measures of pasture biomass from many overlapping high-resolution images. Repeated remotely piloted aircraft system measures throughout a growing season, were modelled with persistent photosynthetic pasture responses from various Planet Dove high spatial resolution satellite image-derived vegetation indices. Pasture height modelling as an input to the modelling of yield was assessed against terrestrial laser scanning and reported correlation coefficients (R2) from 0.3 to 0.8 for both a coastal grassland and inland woodland pasture. Accuracy of the predictive modelling from both the remotely piloted aircraft system and the Planet Dove satellite image estimates of pasture yield ranged from 0.8 to 1.8 TSDM(tha−1). These results indicated that the practical application of repeated remotely piloted aircraft system derived measures of pasture yield can, with some limitations, be scaled-up to satellite-borne imagery to provide more temporally and spatially explicit measures of the pasture resource base.

Studies have shown that aerosols generated from flavored e-cigarettes contain Reactive Oxygen Species (ROS), promoting oxidative stress-induced damage within pulmonary cells. Our lab investigated the ROS content of e-cigarette vapor generated from disposable vape bars, a product exempt from the Federal Drug Enforcement Agency’s (FDA) 2020 flavor ban. Specifically, we analyzed vape bars belonging to multiple flavor categories (Tobacco, Minty Fruit, Fruity, Minty/Menthol, Desserts, and Drinks), manufactured by various vendors and of various nicotine concentrations (0-6.8%). Aerosols from these flavored vape bars were generated by a single puff aerosol generator and individually bubbled through a fluorogenic solution to detect and semi-quantify ROS in H2O2 equivalents generated by the vape bars. We compared and contrasted the ROS levels generated by each flavor as an indirect determinant of oxidative stress potential by these disposable vape bars. Our results showed that ROS concentration (μM) of aerosols produced from the vape bars varied significantly between different flavors and a function of nicotine concentration. Likewise, our results suggest that flavoring chemicals and nicotine concentration play a role in alerting ROS production in e-cigarette aerosols. Our study provides insight into the differential health effects of flavored disposable vape bars and the need for their regulation.

Existing methods for building extraction from remotely sensed images strongly rely on aerial or satellite-based images with very high resolution, which are usually limited by spatiotemporally accessibility and cost. In contrast, relatively low-resolution images have better spatial and temporal availability but cannot directly contribute to fine- and/or high-resolution building extraction. In this paper, based on image super-resolution and segmentation techniques, we propose a two-stage framework (SRBuildingSeg) for achieving super-resolution (SR) building extraction using relatively low-resolution remotely sensed images. SRBuildingSeg can fully utilize inherent information from the given low-resolution images to achieve high-resolution building extraction. In contrast to the existing building extraction methods, we first utilize an internal pairs generation module (IPG) to obtain SR training datasets from the given low-resolution images and an edge-aware super-resolution module (EASR) to improve the perceptional features, following the dual-encoder building segmentation module (DES). Both qualitative and quantitative experimental results demonstrate that our proposed approach is capable of achieving high-resolution (e.g. 0.5 m) building extraction results at 2×, 4× and 8× SR. Our approach outperforms 8 other methods with respect to the extraction result of mean Intersection over Union (mIoU) values by a ratio of 9.38%, 8.20% and 7.89% with SR ratio factors of 2, 4, and 8, respectively. The results indicate that the edges and borders reconstructed in super-resolved images serve a pivotal role in subsequent building extraction and reveal the potential of the proposed approach to achieve super-resolution building extraction. Our code is available at https://github.com/xian1234/SRBuildSeg.

Target 12.3 of the United Nations Sustainable Development Goals (SDGs) calls for halving per capita global food waste at the retail and consumer levels, by 2030. The Food Waste Index is suggested as a methodology for grasping the situation. This paper focuses on the consumer level (household food waste). We argue that in order for generating useful information for devising and implementing effective measures for reducing food waste, it should be measured at Level 3 of the Food Waste Index, based on sorting analysis of generated waste, making a distinction between avoidable and non-avoidable food waste. Furthermore, a breakdown by sub-categories that reflect the flow of food in the household could help identify target behaviours. We have developed a categorisation scheme that is internationally agreeable and adoptable, and 1) generates useful information for policy-making and for tackling with reduction of food waste, 2) makes clear the concept of avoidable food waste, and 3) is practical and does not overcomplicate the work of grasping the situation of food wastage. Results of workshops regarding this scheme suggest that the scheme satisfies the criteria. This scheme has been applied to a few sorting analyses of household food waste in Japan, and their results are compared.

This paper discusses the use of a participatory approach to assess the level of understanding of the Water-Energy-Climate Change nexus in South Africa. The aim is to facilitate the development of well-coordinated, systematic, and holistic strategies for efficient management of the nexus and its implications in the country. The assessment was guided by the broader Integrated Water Resource Management framework, which promotes a participatory approach in the administration of water resources. The paper argues that despite the reasonable level of understanding of WECC, there is still a lack of integrated policy development and planning among key stakeholders. This is exacerbated by limited coordination and consultation among these stakeholders, particularly policymakers. This necessitates the urgent adoption of holistic and systems thinking approaches, and the promotion of collaboration among different stakeholders mandated to manage WECC sectors. Until such approaches are adopted, the WECC nexus will continue to impede the country’s socio-economic development and environmental wellbeing.

The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of ecosystems productivity and related climate, topography, and edaphic impacts. The spatio-temporal changes of LAI were assessed throughout Ardabil Province, a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine- GEE was tested against traditional ENVI measures to provide LAI estimations. Besides, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI at large areas in a short time and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including Enhanced Vegetation Index calculated in GEE (EVIG) and ENVI5.3 software (EVIE), as well as Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVIE). Besides, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured on June and July 2020 in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various Plant Functional Types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVIG, EVIE, and NDVIE at Province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), in that respect in July. The highest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVIG-LAI, EVIE-LAI, and NDVIE-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70), ecoregions and in July were for Bilesavar ecoregion respectively with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r&gt;0.83 and R2&gt;0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVIE-LAI in June with r=0.56 and R2=0.31). On average, all three examined LAI measures tended to underestimation compared to LP 100-LAI (r&gt;0.42). The findings of the present study can be promising for effective monitoring and proper management of vegetation and land use in Ardabil Province and other similar areas.

On the 6th September at 03:08AM local time, the Iburi-Hokkaido Earthquake, only 33 km deep triggers >5,000 co-seismic mass-movements in the hills in a 25 km radius from the epicenter. Although the majority of the mass-movements occurred in complex-geometry valley with the coalescence of deposits, a small sub-set of 59 events deposited on the semi-horizontal val-ley-floor generating separated deposits that were studied in the present contribution. The aim of the present contribution was to contribute to the existing databases of empirical relationships based on planform and vertical dataset, and to define the scalars of those relations that charac-terize the mass-movements of the Iburi-Hokkaido earthquake, with the overarching goal of generating predictors for hazard-mapping. To reach these objectives, the methodology relies on LiDAR data flown in the aftermath of the earthquake as well as aerial photographs. Using Geo-graphical Information Science (GIS) tools planform and vertical parameters were extracted to calculate the power-law relations between areas and volume, between the Fahrböschung and the volume of the deposits, as well as other geometric relationships. Results have shown that the relation S=k〖V_d〗^(2/3) where S is the surface area of a deposit and Vd the volume, and k a scalar that is function of S: k=2.1842 ln⁡(S)-10.167 with a R2 of 0.52, and this relation is improved for the open-slope mass-movements but not the valley-confined ones, that present more varia-bility. The Fahrböschung for events that started as valley-confined mass-movements was Fc = -0.043ln(D) + 0.7082 with a R2 of 0.5m while for open-slope mass-movements, the Fo = -0.046ln(D) + 0.7088 with a R2 of 0.52. These results contribute to the growing co-seismic land-slide database and they can also be the base to understand the role of the counter-slopes and complex topography on the spread and distance travelled by the mass-movement deposits.

This work presents updated reconstructions of watershed runoff to San Francisco Estuary from tree-ring data to AD 903, coupled with models relating runoff to freshwater flow to the estuary and salinity intrusion. We characterize pre-development freshwater flow and salinity conditions in the estuary over the past millennium and compare this characterization with contemporary conditions to better understand the magnitude and seasonality of changes over this time. This work shows that the instrumented flow record spans the range of runoff patterns over the past millennium (averaged over five, ten, twenty and one hundred years), and thus serves as a reasonable basis for planning-level evaluations of historical hydrologic conditions in the estuary. Over annual timescales we show that, although median freshwater flow to the estuary has not changed significantly, it has been more variable over the past century compared to pre-development flow conditions. We further show that the contemporary period is generally associated with greater spring salinity intrusion and lesser summer-fall salinity intrusion relative to the pre-development period. Thus, salinity intrusion in summer and fall months was a common occurrence under pre-development conditions and has been moderated in the contemporary period due to the operations of upstream reservoirs, which were designed to hold winter and spring runoff for release in summer and fall. This work also confirms a dramatic decadal-scale hydrologic shift in the watershed from very wet to very dry conditions during the late 19th and early 20th centuries; while not unprecedented, these shifts have been seen only a few times in the past millennium. This shift resulted in an increase in salinity intrusion in the first three decades of the 20th century, as documented through early records. Population growth and extensive watershed modification during this period exacerbated this underlying hydrologic shift. Putting this shift in the context of other anthropogenic drivers is important in understanding the historical response of the estuary and in setting salinity targets for estuarine restoration. By characterizing the long-term behavior of San Francisco Estuary, this work supports decision-making in the State of California related to flow and salinity management for restoration of the estuarine ecosystem.

: The agriculture sector is one of the backbones of many countries’ economies and its processes have been changing in order to enable technological adoption to increase productivity, quality, and sustainable development. In this research, we present a theoretical reflection through a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, the so-called Precision Agriculture (PA) and Agriculture 4.0 (A4.0). To do this, we used 4,694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis (BPNA) of the literature with the support of the PICOC protocol and the SciMAT software. Our findings present 22 strategic themes related to Digital Agriculture (DA) such as Internet of Things (IoT) and Climate-smart Agriculture (CSA) among others, and the thematic network structures of the motor themes and the thematic evolution structure of the field of the study over time. In addition, our results discuss the main challenges and opportunities of DA. Our findings have the potential to provide insights for practitioners and researchers in decision-making and pave the way for future works.

The article studies the Venetsiansky (Hydropark) Island (the Dnipro River, Kyiv, Ukraine) landscape structure applying the genetic landscape science method and the European landscape classification (LANMAP) approach. The aim of the article is to determine the best way to study the river islands landscapes analyzing the Venetsiansky Island landscape structure by the both methods. Methodology. The genetic landscape science method consists in the next steps: 1) the island’s territory information collecting; 2) the preliminary landscape map creating; 3) field study; 4) the final landscape map creating. The LANMAP method consists on: 1) the climate study; 2) the altitude study; 3) the parent material study; 4) the land cover study. The results. The genetic landscape science method demonstrates that the Venetsiansky Island is not a landscape, but a structural part of the landscape – the tract. The LANMAP study reveals that the Venetsiansky Island is naturally homogeneous, but land cover differs. The conclusion. The both methods’ study shows that the river island cannot be the entire landscape by the natural criteria, but only the part of it. The genetic landscape science explores the landscape forming while the LANMAP reveals the current state of the landscape.

The contextual and risk perception of climate change plays a critical role in an individual’s decision-making process. It could also help people to respond appropriately to the consequences of global climate change and eventually take necessary adaptation actions. However, the perceptions of climate change are often gendered and vary among men and women. Therefore, this study explores different perceptions of climate change and its local adaptation options among ultra-poor vulnerable women, particularly in highly vulnerable flood-prone regions of Bangladesh. The research followed an empirical research methodology to collect primary and secondary information using qualitative and quantitative research tools. The study findings reveal that climate change perceptions at the individual level are relatively low (63%). Still, they have been observing significant changes in various climatic variables over the past 30 years. Moreover, this study identified some major adaptation options such as plinth raising (100%), livestock rearing (100%), homestead gardening (82%), seasonal migration (82%), and using indigenous knowledge (69%), and so on to tackle the adverse impacts of climate change-induced extreme events including flooding at the local level. For implementing these adaptation measures, the respondents spent a significant amount of financial resources from individual sources in the study area. Structural Equation Modeling (SEM) is used in addition to the statistical analyses to understand any connections between the climate change perceptions and other variables associated with the community under study. The SEM result shows that climate change will be a long–term problem, which offers a strong predictor in this model, considering standardized regression weight β= 0.56. It means, despite inadequate knowledge on climate change of the respondent’s, climate change is occurring and becoming the worst factor limiting cultural, economic, and environmental development in the study area.

Marine species are declining at an unprecedented rate, catalyzing many nations to adopt conservation and management targets within their jurisdictions. However, marine species and the biophysical processes that sustain them are naive to international borders. An understanding of the prevalence of cross-border species distributions is important for informing high-level conservation strategies, such as bilateral or regional agreements. Here, we examined 28,252 distribution maps to determine the number and locations of transboundary marine plants and animals. Over 90% of species have ranges spanning at least two jurisdictions, with 58% covering more than ten jurisdictions. All jurisdictions have at least one transboundary species, with the highest concentrations of transboundary species in the USA, Australia, Indonesia, and the Areas Beyond National Jurisdiction. Distributions of mapped biodiversity indicate that overcoming the challenges of multinational governance is critical for a much wider suite of species than migratory megavertebrates and commercially exploited fish stocks—the groups that have received the vast majority of multinational management attention. To effectively protect marine biodiversity, international governance mechanisms (particularly those related to the Convention on Biological Diversity, the Convention on Migratory Species, and Regional Seas Organizations) must be expanded to promote multinational conservation planning, and complimented by a holistic governance framework for biodiversity beyond national jurisdiction.

World Economy today depends on business investments that are propelled by Green technology, innovations and entrepreneurial activities. In recent years, developing economies in Asia, Africa and Latin America have embarked on easy capital access to Small Medium Enterprises (SMEs) to facilitate their economic growth. Kenya is among the Middle Level Income Countries that have gained global recognition through entrepreneurial innovations. In this study we assess the role of entrepreneurship towards poverty alleviation in Kenya. The objectives of the study were: to evaluate the role of entrepreneurship in poverty alleviation in Kenya; to identify entrepreneurship innovations and their economic contribution in Kenya and to determine the significance of entrepreneurship to Kenyan economy. Methodology of study took a parametric approach through pure desktop studies on entrepreneurship cases in Kenya. Success case studies of entrepreneurial innovations like M-pesa, M-soko and Uwezo Fund initiatives were assessed. The paper notes that activities undertaken in each of these case studies have made great contributions to poverty alleviation and economic development in both urban and rural areas of Kenya.

This study aligns with the 2030 United Nations Sustainable Development Goals- 3 which aim to “ensure healthy lives and promote well-being for all at all ages”. It contributes to the nascent literature stream on energy-health dynamics by introducing a holistic theoretical model to empirically examine the mediation effect of carbon emissions on the relationship between nonrenewable energy and infant mortality rates. Using an unbalanced panel data on 42 Asia and the Pacific countries from 2005 to 2015 and deploying the structural equation modeling approach, the empirical results are surmised as follows: (i) in regard to the full sample of countries, nonrenewable energy indirectly increases infant mortality rates through increasing carbon emissions. In other words, carbon emissions play a partial mediation role between nonrenewable energy and infant mortality rates; and (ii) for the different income groups, carbon emissions show varying mediation effects. For example, the mediation effects of carbon emissions in lower-middle and upper-middle income countries are found to be similar to those of the full sample of countries. Therefore, based on these findings, we conclude that nonrenewable energy is an essential determinant of infant mortality rates. Policy recommendations are put forward.

The runtime environment is an important concern for self-adaptive systems (SASs). Although researchers have proposed many approaches for developing SASs that address the issue of uncertain runtime environments, the understanding of these environments varies depending on the objectives, perspectives, and assumptions of the research. Thus, the current understanding of the environment in SAS development is ambiguous and abstract. To make this understanding more concrete, we describe the landscape in this area through a systematic literature review (SLR). We examined 128 primary studies and 14 unique environment models. We investigated concepts of the environment depicted in the primary studies and the proposed environment models based on their ability to aid in understanding. This illustrates the characteristics of the SAS environment, the associated emerging environmental uncertainties, and what is expressed in the existing environment models. This paper makes explicit the implicit understanding about the environment made by the SAS research community and organizes and visualizes them.

Considering the negative impacts of climate changes along with the rapid increase in population in Islamic dominated states, e.g., the Middle East, water tension among upstream and downstream states is increasing. Despite the importance of water management in Islamic culture, the role of religion has been under-valued and under-emphasized by the scholars. The paper has sought to compare and contrast Islamic water management principles (IWMP) with international water law principles (IWLP). The findings from this analysis show not only that IWMP are in conformity with IWLP, but that in many cases, IWMP can be more effective. For instance, where international water accords between riparian states of a shared river basin are poorly developed and lack enforcement mechanisms under IWLP, those upstream states can abuse their geographical locations depriving those downstream-ers. In contrast, IWMPs stress the equitable and reasonable use of water resources among upstream and downstream users of a shared watercourse. Moreover, although IWLPs emphasize the conservation and preservation of ecosystems and the environment at the basin level, the inter-basin states especially those upstream can pose significant harm to the ecosystems. On the other side, Islam as the religion of peace, has placed much emphasis on the preservation of nature. For example, the verse, “.... And waste not by excess, for Allah loves not the wasters” [Quran, 7:31], illustrates the importance of the sustainable use of water and the environment. It is argued that if Islamic Water Management Principles are incorporated into the management instrument of Islamic States, the issue of equitable and sustainable use of water among Muslim-dominated riparian states (e.g., Iran, Afghanistan, etc.) will be solved.

Forests constitute a key component of the Earth system but the sustainability of the forest reserves in the semi-arid zone is a real concern since its vegetation is very sensitive to the climate fluctuation. The understanding of the mechanisms for the interaction vegetation-climate is poorly studied in the context of African Sahel. In this study, the characteristics of the vegetation response to the fluctuations of precipitation and temperature is determined for the forest reserve of Fina. Rainfall estimates, air temperature and NDVI are used to establish the lag correlations between fluctuations of vegetation and climate variables at both seasonal and interannual bases. Results shows increasing tendency of NDVI started from the 1990s coinciding the recovery of the rainfall from the 1980s drought and the obtained correlation(r=0.66) is statistically significant (pvalue<0.01). The strongest responses of vegetation to rainfall and temperature fluctuations were found after 30 and 15 days, respectively. Moreover, at shorter time lag (e.g. 15 days) more pronounced vegetation responses to both rainfall and temperature were found in agricultural dominated land while at longer time lag (e.g. 30 days) stronger response was observed in Bare dominated land. The vegetation response to the climate fluctuation is modulated by the land use/cover dynamics. Keywords: NDVI, Rainfall, Air temperature, vegetation response, Fina Forest Reserve, Mali.

The prevalence of corona virus and the novel COVID-19 disease in the entire globe has exacerbated different impact on socioeconomic spectrum in the world, including water use pattern. Thus a research was conducted to examine the comparative use of water during pre- and post-COVID-19 lockdown pattern among post-primary schools in Iwo, Osun State, Nigeria. A survey was conducted among fifteen schools which were randomly selected, but with eight public and seven private schools for the investigation. Both descriptive and inferential statistical techniques were used in data analysis. The results revealed that the major source of water to the schools investigated is ground water which is obtained through hand-dug wells and boreholes. It was further discovered that there was increase in water use during post-COVID-19 lockdown era as a result of the directive by the government that clean water should be provided for hand-washing by all schools regardless of the owner to curtail the spread of COVID-19 disease in the country. One sample t-test also revealed that there was a significant difference in water use at (p<0.01) level. It is recommended that the government and other stakeholders in water sector to ensure that all-time and non-seasonal dependent source of water be provided rather than ground water source which is susceptible to variations in water yields from seasonal variations. This will enable continuous clean water supply, for all purposes, including COVID-19 protocols.

Recently, there has been renewed interest in the performance, functionality, and sustainability of traditional small-scale storage interventions (check dams, farm bunds and tanks) used across India for the improvement of local water security. The Central Groundwater Board of India is en-couraging the construction of such interventions for the alleviation of water scarcity. It is of critical importance to understand the hydrological effect of these interventions at basin scales to maximise their effectiveness. The quantification of small-scale interventions in hydrological modelling is often neglected, especially in large-scale modelling exercises. A bespoke version of the GWAVA model was developed to assess the impact of interventions on the water balance of the Cauvery Basin and two smaller sub-catchments. Model results demonstrate that farm bunds appear to have a negligible effect on the estimated average annual simulated streamflow at the outlets of the two sub-catchments and the basin whereas tanks and check dams have a more significant effect. In-terventions generally were found to increase evaporation losses across the catchment. The model adaption used in this study provides a step-change in the conceptualisation and quantification of the consequences of small-scale storage interventions in large- or basin-scale hydrological models.

As for most Mediterranean countries, groundwater is the main resource for irrigation and drinking supply in most parts of Syria, however this resource suffers from mismanagement. In the study area (Northeast of Mt. Hermon), the lack of information makes water management in this area extremely difficult. Assessing groundwater pollution risk is the most essential issue for water resources management, especially in the regions where complex interaction between climate, geology, geomorphology, hydrogeology, water scarcity and water resource mismanagement exist. This complexity leads to significant complication in determining pollution risk of studied system. In the present work, we adopted an Integrative Approach to assess groundwater pollution risk in the study area. This methodology is based on the analysis of hydrogeological characteristic of aquifer system and the available information about socio-economic context and physio-chemical groundwater condition that might affect this system. This approach allowed us to delineate the groundwater pollution risk map based on the analysis of concerning parameters/ indicators. The degree of risk was assessed based as the sum and average of rating of these parameters and indicators for each subarea. Typically, very high pollution risk index was identified over the Quaternary/Neogene horizon, i.e shallow and unconfined aquifer and in the lower part of Jurassic aquifer. In these two parts, the majority of anthropogenic activities are concentrated. Low pollution risk index was found for the outcropping of low permeable Quaternary basalt at the Southern part of the study area. A moderate pollution index was identified for the low/moderate permeability of silt, clay and marly limestone rich horizons of the major part of Neogene aquifer outside of the intersected zones with Quaternary aquifer and for the Paleogene formations. The spatial analysis shows that about 50% of the study area is characterized as being at very high and high pollution risk index. Hence, the overall natural protective capacity of this area is still poor. This study demonstrates the flexibility of the proposed approach to assess groundwater pollution risk in local complex aquifer system characterized by lack of information and data in order to reduce the risk of future groundwater pollution.

: During the period of COVID-19, the Chinese government implemented a series of actions to prevent the spread of the virus. It is noticed that these preventive actions have generated positive effects on air pollution in Wuhan and Beijing. And, due to the differences in city functions, geographic locations, meteorological conditions, and preventive action details between the two cities, noticeable difference is observed on how they reduced air pollution. This unfortunate incident has become a social sample for studying the industrial and livelihood activities impact on air pollution, otherwise would be highly impossible. This paper starts from observing data from NASA's real-time fine particulate matter (PM2.5) and NO2, and comparing the air pollution in this special time domain with previous years. It is discovered that both PM2.5 and NO2 have been reduced in Wuhan, while only NO2 has significant reduction in Beijing, during the COVID-19 responses. This suggests that the human activity suppression by the COVID-19 control yields different effects on different pollutants and in different cities. Possible reasons for such effects are analysed by considering the public health control levels as well as the pollutant migration, industrial activities, and the weather conditions.

The disastrous 2017 fire season in Portugal lead to widespread recognition of the need for a paradigm shift in forest and fire management. We focused our study on Alvares, a parish in central Portugal which had 60% of its area burned in 2017, with a large record of historical. We evaluated how different fuel treatment strategies can reduce wildfire hazard in Alvares, through i) a fuel break network with different priorities and ii) random fuel treatments resulting from stand-level management intensification. To assess this, we developed a stochastic fire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast, and center-east areas of the parish that are very often associated with high fire line intensities. The different fuel treatment scenarios decreased burned area between 12.1-31.2%, resulting from 1%-4.6% increases in annual treatment area, and reduced 10%-40% the likelihood of wildfires larger than 5000 ha. On average, simulated burned area decreased 0.22% per each ha treated, and effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

Long-term dewatering of groundwater is a necessary operation for mining safety in open-pit coal mines, while extensive dewatering might cause ecological problems due to dramatical changes of moisture movement in the soil, especially in ecological-fragile areas. This paper presents a quantitative methodology to evaluate the impact of the coal mining operation on moisture movement in the vadose zone by taking the Baorixile open-pit coal mine as an example. A long-term in-situ experiments（from 2004 to 2018), laboratory analysis and numerical modelling were conducted to analyse the mechanisms and relationship among the dropping groundwater level, the vadose-zone moistures, and the ecological responses in the grassland area. The experiment data and modelling results suggest that groundwater level dropping during open-pit mining operation has limited influence on the vadose zone, exhibiting a variation of capillary water zone within a depth of 3 m while the vadose zone and soil water zone were at least 16 m deep. The critical evaporation depth of ground water is 8 m. The long-term influence radius of groundwater dewatering is about 2.72 km during the Baorixile mining operation, and the groundwater level change mainly influences the lower part of the intermediate vadose zone and the capillary water zone below 16 m, with little influence on the moisture contents in the soil water zone where the roots of shallow vegetation grow. The results from this study provide useful insight for sustainable development of coal mining in ecological-fragile areas.

In this work, we propose simple and robust technique for the retrieval of underlying surface spectral albedo using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi - zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral albedo for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.

The use of swine manure as a source of plant nutrients is one alternative to synthetic fertilizers. However, conventional manure application with >90% water and a low C:N ratio results in soil C loss to the atmosphere. Our hypothesis was to use biochar as a manure nutrient stabilizer that would slowly release nutrients to plants upon biochar-swine manure mixture application to soil. The objectives were to evaluate the impact of biochar-treated swine manure on soil total C, N, and plant-available macro and micronutrients in greenhouse-cultivated corn (Zea mays L.) and soybean (Glycine max (L.) Merr.). Neutral pH red oak (RO), highly alkaline autothermal corn stover (HAP), and mild acidic Fe-treated autothermal corn stover (HAPE) biomass were pyrolyzed to prepare biochars. Each biochar was surface-applied to swine manure at a 1:4 (wt/wt) ratio to generate mixtures of manure and respective biochars (MRO, MHAP, and MHAPE). Conventional manure (M) control and manure-biochar mixtures were then applied to the soil at a recommended rate. Corn and soybean were grown under these controls and treatments (S, M, MRO, MHAP, and MHAPE) to evaluate the manure-biochar impact on soil quality, plant biomass yield, and nutrient uptake. Soil OM significantly (<0.05) increased in all manure-biochar treatments; however, no change in soil pH or N was observed under any treatment. No difference in soil ammonium between treatments was identified. An increase (p<0.05) in soil nitrate under corn was observed for conventional manure (M) treatment. There was a significant decrease in soil M3-P for all manure-biochar treatments compared to the conventional M, but that did not impact plant nutrient uptake. No statistical difference in corn or soybean biomass yield or plant nutrient uptake was observed in the short, two-month experiment. Interestingly, manure-biochar application to soil significantly diluted the M3-extractable soil Cu and Zn concentrations. The results attribute that manure-biochar has the potential to be a better soil amendment than conventional manure application to the soil.

The ubiquity of amino acids in carbonaceous meteorites has suggested that amino acids are widespread in the Universe, serving as a common class of components for the emergence of life. However, parameters for modeling amino acid polymerization at mineral–water interfaces remain limited, although the interfacial conditions inevitably exist on planets with surface liquid water. Here, we present a set of extended triple-layer model parameters for aspartate (Asp) and aspartyl-aspartate (AspAsp) adsorptions on ferrihydrite, anatase, and γ-alumina determined based on the experimental adsorption data. By combining the parameters with the reported thermodynamic constants for amino acid polymerization in water, the impacts of these minerals on Asp dimerization are calculable over a wide range of environmental conditions. It was predicted, for example, that ferrihydrite strongly increases the AspAsp/Asp equilibrium ratio in neutral to acidic pH; the ratio in the adsorbed state reaches 40% even from a low Asp concentration (0.1 mM) at pH 4. This percentage is approximately 5 × 107 times higher than that attainable without mineral (8.5 × 10–6%). Our exemplified approach enables us to screen wide environmental settings for abiotic peptide synthesis from a thermodynamic perspective, thereby narrowing down the geochemical situations to be explored for life’s origin on Earth and Earth-like habitable planets.

With the rapid development of urbanization and industrialization in China, environmental issues have become a knotty problem, especially issues related to air, water, and solid-waste pollution. These pollutants pose threats to the health of the population and to that of communities and have a vicious influence on the healthcare system. Additionally, pollution also exhibits spill-over effects, which means that pollution in the local region could affect the healthcare services in a neighbouring region. Therefore, it is necessary to explore the relationship between pollution and healthcare. A spatial autocorrelation analysis was conducted and spatial panel econometric models were constructed to explore the characteristics of pollution and healthcare services in China and the relationship between them using data on all 31 provinces over twelve consecutive years (2006-2017). The results showed that the utilization of healthcare services and environmental pollution were not randomly distributed; unsurprisingly, air pollution and solid-waste pollution were mainly found in parts of northern China, while water pollution was highest in southern and coastal China. In addition, environmental pollution exhibited spill-over effects on healthcare services. For example, a 1% increase in solid waste in one specific geographical unit was estimated to increase the inpatient visits per capita in adjacent counties by 0.559%. Specifically, pollution showed different degrees of influence on healthcare services, which means that the impact of environmental pollution on the number of outpatient visits is greater than on the number of inpatient visits. Our results provide the government with evidence for effectively formulating and promulgating policies, especially policies aimed at tackling spill-over effects among different regions.

Sustainable Development Goal 12 requires countries to achieve responsible consumption and production patterns without exceeding safe environmental limits for natural resource use. However, little is known about how cropland impacts from the agri-food sector contribute to the exceedance of national environmental limits for consumption and production. Using a multi-regional input-output model, we linked the cropland impacts of agri-food production to countries of consumption while considering the exceedance of production-based and consumption-based environmental limits. We defined national consumption-based environmental limits via the fair-share approach and quantified national production-based environmental limits according to the biophysical limit of available arable land. We then classified countries into quadrants according to their exceedance of consumption and/or production environmental limits. We found that the USA, Australia and other high-income countries were exceeding both consumption-based and production-based environmental limits. High-population but low-income countries such as India and China were within safe consumption-based environmental limits but exceeded production-based environmental limits. Brazil and other countries of the Americas incurred substantial environmental costs due to the conversion of forests into cropland to produce food for export. We identified patterns in international trade relationships that could inform national-level responsible agri-food consumption and production patterns across the global supply chain, thereby contributing to Sustainable Development Goal 12. More stringent regulations and commitments in national and international policies are required to reduce the exceedance of consumption-based and production-based environmental limits and avoid exceeding the global land-system change planetary boundary.

Consumer products contain the chemical substances that threaten human health. The modeling methods and experimental methods have been used to estimate the inhalation exposure concentration by the consumer products. The model and measurement methods have the spatial property problem and time/cost consuming problem, respectively. For solving the problems due to the conventional methodology, this study performed the feasibility of applying CFD for evaluation of inhalation exposure by comparing the experiment results and the zero-dimensional results with CFD results. To calculate the aerosol concentration, the CFD was performed by combined the 3D Reynolds averaged Navier Stoke’s equation and discrete phased model using ANSYS FLUENT. As a result of comparing the three methodologies performed under the same simulation/experimental conditions, we found the zero-dimensional spray model shows approximately 5 times underestimated inhalation exposure concentration when compared with the CFD results and measurement results in near field. Also, the results of the measured concentration of aerosols at five locations and the CFD results at the same location were compared to show the possibility of evaluating inhalation exposure at various locations using CFD instead of experimental method. The CFD results according to measurement positions can predict rationally the measurement results with low error. In conclusion, in the field of exposure science, a guideline for exposure evaluation using CFD was found that complements the shortcomings of the conventional methodology, the zero-dimensional spray model and measurement method.

Monitoring crown closure evolution using multi-temporal Light Detection and Ranging (LiDAR) surveys is a method that we expect to be increasingly adopted given the availability of LiDAR sensors and the accumulating survey archives. However, little attention was devoted to comparing crown closure estimates from independent surveys. Although survey parameters cannot be modified after the data collection, we speculate that the error associated to crown closure estimates comparison can be reduced by selecting optimal post-survey parameters. In this study, we compared crown closure estimates of three airborne LiDAR surveys from 2018 (40 pt/m²) used as a reference, and two lower-density surveys from 2016 (4.5 pt/m²) and 2018 (2 pt/m²). We studied the effect of the height threshold used to separate canopy points and the grid resolution, using skewness and variance of lagged difference of crown closure. Crown closure estimates using low height thresholds were more different across surveys, resulting in higher root mean squared error (RMSE), bias and more different variograms. Results show that optimal height threshold was 3 m and grid resolution was 25 m, although there was room for decision (RMSE of 7% and 5%, and bias of 4% and 0% for 2016 and 2018 low-density surveys).

Nature-based Solutions (NbS) have rapidly been gaining traction across the research, policy, and practice spheres, touted as transformative actions to jointly address biodiversity loss and climate change. However, there are multiple, alternative ways to imagine NbS in those three spheres. To inform the NbS discourses across these three spheres, we critically reflect on the prevailing framing of NbS and consider the potential of a different framing of NbS to support transformations towards regenerative relationships between humans and nature. Such reflection is urgently needed to ensure that research, policy, and practice delivers on the transformative ambitions of NbS. We propose a novel “core framing” of NbS, charting two pathways for how such a framing can support a human value-based transformation – first through influencing individual beliefs and values, and second through the communication and application of the NbS concept in research, policy, and practice. We argue that for NbS to support transformation, it must support a reframing of human-nature relationships, one where the interdependencies between people and nature are recognized as essential for social and environmental well-being. We elaborate on how such a framing is key to support inclusivity and collaboration between diverse research perspectives, policy objectives across scales, and implementation practices, to deliver successful NbS.

The forest transition – or forest-area transition – has been put forward as a land-use concept by A.S. Mather in 1992 (The forest transition. Area 24, 367-379), to describe the historical trend generally observed in the forest area of developed countries, embodied in a V-shaped curve of the forest area over time, and that may serve as a paradigm to understand and anticipate deforestation in the developing world. Well in line with a geographical approach to forests, forest transition has thus been defined as one-dimensional, forest area being the reference state variable. From a forestry perspective, the analysis appears to be reductive, as forests are described by many other state variables than area, including forest growing stock, composition in tree species, or stand structure. Whether the drivers of forest transition (population dynamics, economic modes of production and consciousness, as classified by Mather) also impact these other forest state variables in a general way thus comes forth as a logical issue.From a deductive analysis of forest transition drivers, and from forest trends brought to light in Europe, France, and at other places in the world, we here argue that the forest transition concept can be extended to a multi-dimensional space of forest attributes, characterized by typical ideal dynamics. Cumulative impacts onto forests and irreversible losses in forest biodiversity over a forest transition are hence highlighted. Global change, as a parallel consequence of countries’ developing process, further appears as one additional albeit less coupled dimension of forest transition, as it modifies forest productivity and vitality over time. Since forest ecosystem services and forest profitability primarily depend on such attributes, we argue that the extension of the forest transition concept has significance for land-use change and forest protection issues. A prospect on future changes in the forests of developed countries with the European space as a benchmark is finally proposed that leads to extend the temporal significance of forest transition. Though poorly described, returning forests on abandoned agricultural lands are significant, and deserve greater attention.

Rotary drilling for oil and natural gas uses drilling fluid for lubrication of the bit, to seal off unstable shale layers, and floating out rock cuttings. Drilling fluid is a water-clay chemical mixture. Produced water is a water-sand chemical mixture. Land farming is a common disposal technique of drilling fluid and produced water. In the land farming process, amendments of fluid are repeatedly applied to the soil surface. Plant growth and soil chemical properties may be altered by additions of drilling fluid, because of alkalinity, salinity, trace elements, and petroleum residue contained in waste. The objective of this study was to determine the change in soil pH, electrical conductivity (EC), total nitrogen and carbon, and extractable nutrient levels following the land application of drilling fluid and produced water. The study was a comparison of three plots with similar soil properties and conditions. The three study plots had various levels of drilling fluid and produced water applications. The data show a major difference from field-to-field for EC, Na, and Cl levels. The EC and salt levels increased with additional applications of drilling fluid and produced water. The percent total nitrogen values and plant available P levels were very low in all fields. High EC and salt values, coupled with low N and P levels, would be detrimental to plant growth and development. To successfully vegetate this land-farm site, application of N and P fertilizer would be required. This study will help to give a better understanding of practical ways to land-farm drilling fluid and produced water in a fashion that both minimizes environmental issues and is economically feasible. Salinity changes to soil were expected to be high; there are excessive amounts of sodium and chloride in spent drilling fluid and produced water.

The subject of this article is the dynamics of water in a soil pedostructure sample whose internal environment is subjected to a potential gradient created by the departure of water through surface evaporation. This work refers entirely to the results and conclusions of a fundamental theoretical study focused on the molecular thermodynamic equilibrium of the two aqueous phases of the soil pedostructure. The new concepts and descriptive variables of the hydro-thermodynamic equilibrium state of the soil medium, which have been established at the molecular level of the fluid phases of the pedostructure (water and air) in a previous article, are recalled here in the systemic paradigm of hydrostructural pedology. They allow access to the molecular description of water migration in the soil and go beyond the classical mono-scale description of soil water dynamics. We obtain a hydro-thermodynamic description of the soil's pedostructure at different hydro-functional scale levels including those relating to the water molecule and its atoms. The experimental results show a perfect agreement with the theory, validating at the same time the systemic approach which was the framework.

Net CO2 emissions and sequestration from European forests are the result of removal and growth of flora. To arrive at aggregated measurements of these processes at a country's level, local observations of increments and harvest rates are up-scaled to national forest areas. Each country releases these statistics through their individual National Forest Inventory using their particular definitions and methodologies. In addition, five international processes deal with the harmonization and comparability of such forest datasets in Europe, namely the IPCC, SOEF, FAOSTAT, HPFFRE, FRA (definitions follow in the article). In this study, we retrieved living biomass dynamics from each of these sources for 27 European Union member states. To demonstrate the reproducibility of our method, we release an open source python package that allows for automated data retrieval and analysis, as new data becomes available. The comparison of the published values shows discrepancies in the magnitude of forest biomass changes for several countries. In some cases, the direction of these changes also differ between sources. The scarcity of the data provided, along with the low spatial resolution, forbids the creation or calibration of a pan-European forest dynamics model, which could ultimately be used to simulate future scenarios and support policy decisions. To attain these goals, an improvement in forest data availability and harmonization is needed.

COVID‑19 pandemic, also known as the coronavirus pandemic, has spread rapidly across the globe since the end of 2019 and brought impressive changes in our life and living through partial or full lockdown and reduced anthropogenic activities. Hence, it is imperative to investigate the impacts and consequences of COVID-19 on global eco-system and environment. The present study accordingly addresses the impacts and consequences of COVID-19 by ten environmental indicators; viz., global warming (or greenhouse gas emission), stratospheric ozone depletion, ozone formation (on human health), fine particulate matter formation, smog, ionizing radiation, human carcinogenic toxicity, human non-carcinogenic toxicity, water resource consumption, and effect on human health. The overall study has been performed in agreement with the standard principle and guidelines of life cycle assessment. Worldwide changes in consumption of fossil fuels, viz., petroleum, coal and natural gas, as a result of COVID-19 pandemic, has been the core theme of the study. Outcomes from the study show that COVID-19 has been a ‘blessing in disguise’ for the global environment with most of the above-mentioned indicators declining by approximately 20-30% in 2020 in comparison to the 2019 level.

This study focuses on traffic condition analysis, especially in under developing country India and makes more visible of traffic flow by using traffic flow theory in order to understand real traffic condition. India is one of rapid economic growing countries and large market with second largest population 1.3 billion in 2018. On the other hand, there are social issues such as environment air pollution and global warming by traffic CO2 emission of transportation. This kind of condition is not only in India, but in other South East Asia and Africa in future. From recent more than one-month traffic observation in a typical major city Ahmedabad in Gujarat state, which has about 8 million population and industrialized city. In terms of traffic data collection, 14 CCTV cameras are used in the city. Based on multiple traffic cameras monitoring, author found the unique traffic flow characteristics and compares traffic flow theory. In this study, it is described what is key parameters to show real traffic congestion condition and how these congestion occurs.

The accurate assessment and monitoring of soil erosion is of great significance for guiding food production and ensuring ecological security, and it is a current research hotspot. In this paper, remote sensing and geographic information systems (GISs) are combined with the Revised Universal Soil Loss Equation (RUSLE model) to carry out research on soil erosion monitoring and make a quantitative evaluation. According to five factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, crop management and water and soil conservation measures, the distribution of the soil erosion rate in Jilin Province in 2019 was mapped, and the soil erosion rate was divided into 5 levels according to the degree of erosion, including very slight, slight, moderate, severe and extremely severe erosion. Based on the segmented S-slope factor model and the unique topographical features of the study area, the relationships among the soil erosion rate, erosion risk level, erosion area, erosion amount and slope angle (θ) were systematically analysed, and a slope angle of 15° was identified as the threshold for soil erosion on sloped farmland in Jilin Province. The total soil erosion in Jilin Province was 402.14×106 t in 2019, the average soil erosion rate was 21.6 t·ha-1·a-1, and the average soil loss thickness was 1.6 mm·a-1; these values were far greater than the soil erosion rate risk threshold of 10 t ·Ha-1·a-1. Thus, the province has a strong level of soil erosion. We conclude that soil degradation is accelerating, and food production and the ecological environment will face severe challenges. It is suggested that soil erosion control should be carried out according to different types and slopes of land, with an emphasis on the management of forestland and farmland because forestland and farmland are currently the first types of land to be managed in Jilin Province. This paper aims to explore a timely, fast, efficient and convenient soil erosion monitoring and evaluation method and provide effective monitoring tools for agricultural water and soil conservation, ecological safety management and stable food production in Jilin Province and similar black soil areas.

The Kenya Forestry Service permits rental of low-density national forest areas for use as common farmland, but public access to such areas is restricted to prevent deforestation against a background of rising demand for fuel wood. This study was conducted to clarify characteristics relating to the production of indigenous bamboo (a useful wood resource) by the approximately 23% of locals who work on common farmland in central Kenya’s Kamae forest management area, with estimation to determine above-ground biomass. The results showed that bamboo still represents 60% of such biomass, indicating sustainability in the industry.

Increased exposure to artificial light at night can affect human health including disruption of melatonin production and circadian rhythms and extend to increased risks of hormonal cancers and other serious diseases. In addition, multiple negative impacts on fauna and flora are well documented, and it is a matter of fact that artificial light at night is a nuisance for ground-based astronomy. These impacts are frequently linked to the colour of the light or more specifically to its spectral content. Artificial light at night is often mapped by using space borne sensors, but most of them are panchromatic and thus insensitive to the colour. In this paper, we suggest a method that allows high resolution mapping of the Artificial light at night by using ground-based measurements with the LANcube system. The device separates the light detected in four bands (Red, Green, Blue, and Clear) and provides this information for six faces of a cube. We found relationships between the LANcube’s colour ratios and 1- the Melatonin Suppression Index, 2- the StarLight Index and 3- the Induced Photosynthesis Index. We show how such relationships combined with data acquisition from a LANcube positioned on the top of a car can be used to produce spectral indices maps of a whole city in a few hours.

Rubbish in a forest environment is a great threat to this ecosystem, but this threat may also apply to the lost benefits for visitors to the forest. Previous studies proved that forest areas have a positive effect on obtaining psychological relaxation in the people visiting them. However, it was not known whether this restorative experience could be disturbed in any way by the presence of an open dump in the forest. To check how the presence of a landfill affects the visitors, an experiment was planned in which the respondents observed a forest area with a landfill and a forest landscape without a landfill for 15 minutes (control). The respondents then assessed the landscape using the semantic differential method and the Perceived Restorativeness Scale (PRS). An analysis of these observations showed that the presence of a landfill in the forest significantly changed the appreciation of the landscape by the respondents, the values of positive experiences decreased, and the negative experiences increased. Restorativeness was also reduced. Based on the results, it can be concluded that the presence of garbage in the forest may interrupt the restorative experience of its visitors.

rdinary people and political leaders must know the sources of greenhouse gas emissions and their effect on global climate change before they have ability to make decisions to reduce emissions and increase sinks of these gases. These people must, however, understand where greenhouse gas emissions are formed and how reductions can be made: they must understand where carbon dioxide sinks are and how to preserve or increase these sinks. North Savo is the example used in this work to describe the present emissions and sinks. There are proposals on what should and could be done to reduce greenhouse gas emissions caused by traffic, heating, forests and agriculture. There are possibilities of reducing emissions of greenhouse gases in traffic and heating in spite of the fact that the province has a low population density with long distances between homes and workplaces and schools, and a cold climate. We believe that research will also find solutions for reducing greenhouse gases and protecting waters, which are used for recreational purposes and for raw water of drinking water in many places. Luckily forests cover large areas of North Savo and their growth is an important carbon dioxide sink. In addition, forest soils serve as a valuable storage of carbon. Besides carbon dioxide emissions, emissions of nitrous oxide and methane must also be considered since they are more potent greenhouse gases than carbon dioxide and land use can thus influence these gas emissions.

Carbon and nitrogen contents and their isotopic components and AMS radiocarbon dating ages were measured for 57 coastal sediments from Weizhou Island to analyze the distribution of total inorganic carbon (TIC) and its carbon and oxygen isotopic components (δ13Ccarb and δ18Ocarb), total organic carbon (TOC) and total nitrogen (TN) contents and their stable isotopic components (δ13CTOC and δ15NTN) and environmental significance. The results showed that the oldest age of coastal sediments on Weizhou Island was 2750 cal. a BP, and the average TIC contents of A1, A2, B1, C1, and D1 in the intertidal zone were all greater than 5%, where δ13Ccarb and δ18Ocarb were enriched, while the TIC contents in A3, C2, and D2 of the supra-tidal zone were low, where δ13Ccarb and δ18Ocarb were depleted. Moreover, TIC decreased sharply from the estuary to upstream region in the C1-C2 section. The average C/N ratio was 7.02, and δ13CTOC and δ15NTN were between -14.96‰~-27.26‰ and -14.38‰~4.12‰, respectively. These measurements indicated that the TIC in coastal sediments mainly came from seawater. A1, A2, and B1 in the northern intertidal zone exhibited organic terrestrial signals because of C3 and C4 plant inputs, which proved that the important source of the northern coast of Weizhou Island came from the island. The lacustrine facies deposits were mainly distributed in the upper reaches of the river, the northern coastline was rapidly advancing toward the sea, and part of the southwestern coastal sediments rapidly accumulated to the shore under the influence of a storm surge. The relative sea level of the Weizhou Island area has continuously declined at a rate of approximately 2.07 mm/a, using beach rock as a marker, since the Holocene.

It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

Image fusion is a useful tool for producing a high-resolution multispectral image to be used for land use and land cover mapping. In this study, we use nine pansharpening algorithms namely Color Normalized (CN), Gram-Schmidt (GS), Hyperspherical Color Space (HCS), High Pass Filter (HPF), Nearest-Neighbor Diffusion (NND), Principal Component Analysis (PCA), Resolution Merge (RM), Stationary Wavelet Transform (SWT), and Wavelet Resolution Merge (WRM) to fusion Worldview-3 multispectral Bands and panchromatic band. In spectral and spatial fidelity, several image quality metrics are used to evaluate the performance of pansharpening algorithms. The SWT and PCA algorithms showed better results compared to other pansharpening algorithms while GS and CN algorithms showed the worst results for the original image fusion. The effect of fusion on each band was separately investigated and according to the calculations, we found that the CoastalBlue band and the Blue band showed the best result and the NIR-1 band and NIR-2 band show the worst result for the original image fusion. In the end, we conclude that the choice of fusion method depends on the requirement of remote sensing application.

Biochar application to the soil can improve soil quality and nutrient leaching loss. Recent studies have reported that surficial application of biochar to stored swine manure can reduce emissions of odorous compounds and reduce the volatilization loss of ammonia. Our working hypothesis was that the biochar-treated manure application to the soil would decrease nutrient leaching from manure and increase plant-available nutrients. The study objectives were to evaluate the impact of biochar-treated swine manure on soil total C, N, and other major and minor nutrients. Three biochars (i) neutral pH red-oak (RO), (ii) highly alkaline autothermal corn (Zea mays) stover (HAP), and (iii) mild acidic Fe-treated autothermal corn stover (HAPE) were incubated with swine manure for a month. The biochar-manure mixture was applied in triplicate to soil columns with application rate determined by the P₂O₅-P content in manure or manure-biochar mixtures after the incubation. The ammonium (NH₄⁺), nitrate (NO₃^-), and reactive P concentrations in soil column leachates were recorded for eight leaching events. Soil properties and plant-available nutrients were compared between treatments and control manure & soil. Manure-(HAP&HAPE) biochar treatments significantly increased soil organic matter (OM) and increased soil total C, N, and improved soil bulk density. Concentrations of KCl-extractable NH₄⁺ and NO₃^- significantly increased in HAPE column leachates during this 4-week study and in the soil after the experiment. A significant reduction in soil Mehlich3 Cu was also observed for the manure-HAPE mixture compared with the control. Overall, the manure-biochar incubation enabled biochar to sorb nutrients from manure, and the subsequent manure-biochar mixture application to soil improved soil quality and plant nutrient availability in comparison to conventional manure application to soil. This proof-of-the-concept study suggests that biochars could be used to solve both environmental and agronomic challenges and further improve the sustainability of animal and crop production agriculture.

Despite continued efforts by educators, UN declarations and numerous international agreements, progress is still limited in handling major global challenges such as ecosystem collapse, accelerating climate change, poverty and inequity. The capacity to collaborate globally on addressing these issues remains weak. This systematic review of research on global learning for sustainable development (GLSD) aims to clarify the diverse directions research on GLSD has taken, to present the historical development of the research area, and highlight emerging research issues. The review summarises key findings of the English language literature in the period 1994-2020 identified with the search terms “global learning” and “sustainable development”, sustainability or GLSD, respectively. The review documented a gradually growing knowledge base, mostly authored by scholars located in the global North. Conclusions point to what we might achieve if we could learn from one another in new ways, moving beyond Northern-centric paradigms. It is also time to re-evaluate core assumptions that underlie education for sustainable development more generally, such as a narrow focus on formal learning institutions. The review provides a benchmark for future reviews of research on GLSD, reveals the emerging transformative structure of this transdisciplinary field, and offers reference points for further research

The retrieval of sun-induced chlorophyll fluorescence is greatly beneficial to studies of marine phytoplankton biomass, physiology, and composition and is required for user applications and services. Customarily phytoplankton chlorophyll fluorescence is determined from satellite measurements through a fluorescence line-height algorithm using three bands around 680 nm. We propose here a modified retrieval, making use of all available bands in the relevant wavelength range with the goal to improve the effectiveness of the algorithm in optically complex waters. For the Ocean and Land Colour Instrument (OLCI) we quantify a Fluorescence Peak Height from fitting a Gaussian function and related terms into the top-of-atmosphere reflectance bands between 650 and 750 nm. This algorithm retrieves, what we call Fluorescence Peak Height from fitting a Gaussian function upon other terms to top-of-atmosphere reflectance bands between 650 and 750 nm. This approach is applicable to Level-1 and Level-2 data. We find a good correlation of the retrieved fluorescence product to global in-situ chlorophyll measurements, as well as a consistent relation between chlorophyll concentration and fluorescence from radiative transfer modelling and OLCI/in-situ comparison. The algorithm is applicable to complex waters without needing an atmospheric correction and vicarious calibration and features an inherent correction of small spectral shifts, as required for OLCI measurements.

This document describes the theoretical basis of the algorithms used to determine properties of snow and ice from the measurements of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3 satellites within the Pre-operational Sentinel-3 snow and ice products (SICE) project: http://snow.geus.dk/. The code used for the SICE retrieval and its documentation can be found at https://github.com/GEUS-SICE/pySICE. The algorithms were developed after the work from Kokhanovsky et al. (2018, 2019, 2020).

The detection of hormones, pharmaceutical and personal care products (PPCPs), in aqueous complex media as water bodies is an urgent and mandatory matter because of its harmful impact on the environment. This work presents a sensor device which is able to detect trace of the synthetic hormone 17α-ethinylestradiol (EE2), in a range of concentration of 10-15 to 10-9 M in both mineral and tap waters. These types of water were studied due to their different degrees of complexity, which allow to attain a better understanding of EE2’s behavior and response in different media. The sensor body consists of solid supports having interdigitated electrodes without and with a thin film deposited on it, and device response is evaluated through impedance spectroscopy. The thin films were prepared by the layer-by-layer technique from aqueous solutions of polyethylenimine (PEI) and poly(sodium 4-styrenesulfonate) (PSS) polyelectrolytes. Results demonstrated that it is possible to discriminate clearly the different waters used and to detect EE2, obtained from the second principal component (PC2) as a result of the application of principal component analysis method, with a sensitivity of -0.072 ± 0.009 and -0.44 ± 0.03 per decade of concentration, for mineral and tap water, respectively. Detection limits values were found to be of 8.6 fM (2.6 pg/L) and of 7.5 fM (22.2 pg/L) for TW and MW, respectively and are lower than the ones found in literature. Moreover, the achieved constant proportionality between the PC2 values for each EE2 concentration reveals that one can use this methodology to quantify EE2 concentration in unknown aqueous complex matrices.

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of surface-groundwater interaction, have not been yet investigated. Here, we assess long-term trends in baseflow, quickflow, and streamflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that over 82% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend (< -20 m3 s-1 y-1) along the SFR with spatial agreement between decreased baseflow, increased ET, and irrigated agricultural land. We also noted a decrease in TWS across the SFB with trends exceeding -20 mm y-1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) is providing the observed reduction in total SFR flow. A lack of significant P trends indicates that only P variability likely has not caused the observed baseflow reduction, mainly in the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may be likely a driver of water scarcity over the SFB.

Boreal forests are one of the largest stores of carbon on Earth, and two-thirds of them are located in Siberia. Despite the fact that these forests have a significant influence on the global climate, they continue to remain understudied. Chernevaya taiga is a unique example of a highly productive Siberian boreal ecosystem. This type of forest is characterized by a series of unique ecological traits, the most notable of which are the gigantism of the perennial herbaceous plants and bushes, complete lack of moss cover on soil surface, and the type of soil it grows on, notable for its particularly high rate of decomposition of vegetative remains and low humic acid content. Abundant rainfall actively washes out nutrients from the top layers of the soil, but its fertility level remains very high. In fact, based on the existing data, it is twice as high as that of fertilized agricultural lands. In some ways the conditions within this type of forest closely resemble those observed in tropical rainforests. Microbiota associated with soil and plants represent an integral part of an interconnected system and contribute significantly to productive processes in soils. Its impacts on the environment require further study, since it could lead to discoveries that will help improve soil fertility without harming the natural environment.

COVID-19, previously known as “2019 novel coronavirus”, is a newly discovered virus which causes severe acute respiratory syndrome, similar to corona virus 2 (SARS-CoV-2), which has spread widely through human to human contact and was declared a pandemic by the WHO in March 2020. To cope with this pandemic many countries have adopted nationwide lockdowns which restrict nonessential activities and encourage their populations to avoid public transport, work from hone wherever possible, and to maintain social distancing at all times. While the severity of these shutdowns has varied with country, large geographic regions of the world (including China, India, Iran, Italy, Spain, and the USA) have all been severely affected, not just in the loss of human life, but also in terms of the financial impacts the lockdowns will have on their countries future prosperityIt was previously reported that a number of environmental factors, including humidity and temperature, played an important role in development and spread of the SARS-Corona Virus infection with the virus retaining viability for over 5 days at temperatures between 22–25^oC and relative humidity (RH) of 40–50%. Whereas, elevated temperatures and higher RH (38^oC, and >95% RH) decreased virus viability (Kroumpouzos et al., 2020). The spread of COVID-19 started in low temperature areas of China, with major outbreaks subsequently occurring in Iran, Japan, Northern Italy and South Korea. These new virus epicenters all had similar temperature and latitude, along the 30-50^◦N” zone. Subsequently, the virus was spread to regions of elevated temperature, such as India, the Middle East and Thailand, due to international travel (Kroumpouzos et al., 2020).The aim of this study was to consider the environmental impact of COVID-19, including water pollution. The paper is divided into four sections. In the first section the current literature related to COVID-19 is reviewed. In the second section a recent update on COVID-19 globally is presented, followed by a descriptive impact on the environment in the third section and finally in the fourth section the COVID-19 related worldwide environmental impact is discussed. Since COVID-19 is a currently an active pandemic with no end in sight, while constructive conclusions can only be made on the limited data currently, which may be prone to high errors. However, these conclusions may provide some preliminary suggestions for assisting in assessing spreading patterns of COVID-19 across the globe, and may be of long-term significances with respect to assessing the environmental impact of lockdown policies due to COVID-19 worldwide.

UN 2030 Sustainable Development Goal 6 presents difficulties for small island developing states such as the Kingdom of Tonga, which relies on rainwater and groundwater lenses for freshwater supply. Planning and managing water resources to supply demands in dispersed small islands under variable climate and frequent extreme events is challenging. Tensions between water planning using top-down versus bottom-up processes have long been recognized. Tonga’s overarching national planning instrument is the Tonga Strategic Development Framework, 2015-2025 (TSDFII). This identifies desired national outcomes and is used to direct and resource Ministries and address international and regional commitments. Water supply was a low priority in the three-month consultations that led to TSDFII. Community Development Plans (CDPs), developed by rural villages throughout Tonga’s five Island Groups over nine years, involved participation from 80% of each village population who ranked local priorities. Analysis of priorities in 117 available village CDPs reveals improvements to village water supply was the highest overall priority in all five Island Groups and ranked within the top three priorities by 76% of all villages, with women, youth and men returning figures of 83%, 66% and 80% respectively. The mismatch between top-down and bottom-up priorities appears to result from an urban/rural divide.

The nationwide lockdown imposed to control the spread of novel coronavirus induced dramatic alterations in different sectors of the Nepalese governance including Solid Waste Management (SWM) practices. This study identifies SW collection gaps in nine major cities of Nepal, and highlights the municipal and public hearings on SW management practices before and during the lockdown with a view to emphasize the linkage between Covid-19 and SWM. It includes information on solid waste workers safety practices, collection coverage dynamics, types of vehicles operated for collection and alternative methods adopted by households to manage SW during the collection gaps. It was found that although the coverage of the collection service was similar during the pandemic, there was drastic decrease in the collection frequency leading to a collection gap of 560.58 tons/day and no proper measures were adopted in more than 50% of the households surveyed for SWM during the collection gap. The study reveals poor occupational health and safety practices among the solid waste workers due to unavailability of safety gears and equipment, in spite of being aware of the modes of transmission of the virus. The pandemic exacerbated the challenges of smooth SWM making its significance as an essential service more apparent. This highlights the need of a timely strategic emergency management framework to be developed by the government to continue the invaluable public service without any hindrance.

This work aimed to assess and characterize the air quality in what concerns particulate pollution in urban-industrial environments. The main objectives were to study the spatial variability of the deposition flux of particulate pollution identifying areas with higher deposition, associate the variability with climatological variables and with possible surrounding emitting sources. The method for collecting the deposited particles was based on the standard NF X 43-007. Sampling for particulate pollution took place between April 2015 and February 2016, through seven sampling campaigns. Maps of the spatial dispersion for the particulate pollution were obtained through statistics and geostatistics techniques. Elemental identification by scanning electron microscopy (SEM) was also used but only in two sampling campaigns. The results show that the sampling campaigns that took place during hot and dry periods, 2nd and 3rd, present higher deposition flux: 2.04 g/(m2 x month) and 1.72 g/(m2 x month), respectively. Lower deposition fluxes were registered in the 6th and 7th campaigns: 0.23 g/(m2 x month) and 0.24 g/(m2 x month), respectively. It was also observed a recurrent high deposition at specific sampling points which may be due to both the nearby road traffic and the presence of chimneys. SEM analysis allowed to associate repetitive element deposition, at the same sampling point, to the same emitting source.

Mangroves and salt marshes are among the most productive ecosystems in the global coastal ocean. Mangroves store more carbon (739 Mg CORG ha-1) than salt marshes (334 Mg CORG ha-1), but the latter sequester proportionally more (24%) net primary production (NPP) than mangroves (12%). Mangroves exhibit greater rates of gross primary production (GPP), above-ground net primary production (NPP) and plant respiration (RC) with higher PGPP/RC ratios, but salt marshes exhibit greater rates of below-ground NPP. Mangroves have greater rates of subsurface DIC production and, unlike salt marshes, exhibit significant microbial decomposition to a soil depth of 1 m. Salt marshes release more soil CH4 and export more dissolved CH4 , but mangroves release more CO2 from tidal waters and export greater amounts of POC, DOC and DIC to adjacent waters. Both ecosystems contribute only a small proportion of GPP, RE (ecosystem respiration) and NEP (net ecosystem production) to the global coastal ocean due to their small global area, but contribute 72% of air-sea CO2 exchange from the world’s wetlands and estuaries and contribute 34% of DIC export and 17% of DOC + POC export to the world’s coastal ocean. Thus, both wetland ecosystems contribute disproportionately to carbon flow of the global coastal ocean.

Stormwater management is a key urban issue in the world, in line with the global issues of urban sprawl and climate change. It is urgent to investigate the effectiveness in managing stormwater with different strategies for maintain urban resilience. A method based on a storm water management model (SWMM) was developed for assessing the control of stormwater runoff volume and the percentage removal of suspended solids by implementing a Sponge City strategy. An interdisciplinary approach was adopted incorporating Low Impact Development (LID) with urban Green Infrastructure and Gray Infrastructure paradigms in a typical old residential community in Suzhou, China. Four types of sponge facilities for reducing stormwater runoff were bio-retention cells, permeable pavements, grassed pitches, and stormwater gardens. The simulation results indicate that the stormwater pipe system can meet the management standard for storms with a five-year recurrence interval. The volume capture ratio of annual runoff is 91% and the reduction rate of suspended solids is 56%. This study demonstrates that Sponge City strategy is an effective approach for managing stormwater, particularly in old and densely populated urban areas. Implementing spongy facilities with a LID strategy for stormwater management can significantly enhance urban water resilience and increase ecosystem services.

The COVID-19 pandemic is adversely impacting food and nutrition security and requires urgent attention from policymakers. Sustainable intensification of agriculture is one strategy that attempts to increase food production without adversely impacting the environment, by shifting from water-intensive crops to other climate-resistant and nutritious crops. This paper focuses on the Indian state of Andhra Pradesh by studying the impact of shifting 20% of the area under paddy and cotton cultivation to other crops like millets and pulses. Using FAO’s CROPWAT model, along with monsoon forecasts and detailed agricultural data, we simulate the crop water requirements across the study area. We simulate a business-as-usual base case and compare it to multiple crop diversification strategies using various parameters – food, calories, protein production, as well as groundwater and energy consumption. Results from this study indicate that reduced paddy cultivation decreases groundwater and energy consumption by around 9-10%., and a calorie deficit between 4-8% - making up this calorie deficit requires a 20-30% improvement in the yields of millets and pulses. We also propose policy interventions to incentivize the cultivation of nutritious and climate-resistant crops as a sustainable strategy towards strengthening food and nutrition security while lowering the environmental footprint of food production.

Green Infrastructures (GI) are considered key to reconcile ecological and social benefits by providing multiple functions. The concept is increasingly promoted and guidelines for its implementation have been developed in many countries and regions of the Western Hemisphere. However, for other parts of the world, especially for countries with less developed infrastructures, promotion, guidance for decision-making and manuals for GI are often lacking. But the state of infrastructure development and often unplanned character of settlements in the Global South differ and result in specific constraints as well as demands to GI that need to be addressed explicitly. This study presents a methodological approach to explicitly address the specific conditions and physical limitations to GI development in urban areas of the Global South. A four step methodology was developed to assess the implementation potential for retrofitted and multifunctional urban green infrastructure in public areas. An initial site analysis (1) and the definition of design criteria as well as general strategies (2) to achieve the different dimensions of multi-functionality are the basis to derive spatial typologies (3) for GI elements and finally the spatial suitability assessment for potential placements (4). An application of the methodology to a study area in the metropolitan region of San José, Costa Rica, shows exemplarily that the potential to improve the hydrological conditions (up to 34% of surface runoff reduction), ecological conditions (increase of green space by 2,2 %, creation of 1500 m length of roadside greenery and two new habitat types), and social conditions (2.200 m of road type upgrading) of multi-functionality of the site through Green Infrastructures. These assessment results of different multi-functionality dimension can serve as a guidance for GI promotion and implementation in urban areas of the Global South.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

Forest plantations have a large potential for carbon sequestration, playing an important role in the global carbon cycle. However, despite the huge amount of research carried out worldwide, the absolute contribution of industrial forest plantations is still incomplete for some parts of the world. To contribute to bridge this gap, we calculated the amount of C stock in three fast growing forest species in Chile. Relevant C pools (above-ground and below-ground biomass, forest floor, and soil) were considered for this analysis. Across the industrial plantation forests of Chile, carbon accumulated in the above-ground biomass was 181–212 Mg · ha−1 for Pinus radiata, 147–180 Mg · ha−1 for Eucalyptus nitens, and 95–117 Mg · ha−1 for Eucalyptus globulus (age 20–24 years for P.radiata and 10–14 years for Eucalyptus). Our results agree with other studies showing that 30%–50% of the total C stock is stored in the soil. Total C stocks were for 343 Mg · ha−1 for P.radiata, 352 Mg · ha−1 for E.nitens, and 254 Mg · ha−1 for E. gloubulus, also at the end of a typical rotation. The carbon pool in the forest floor was found to be significantly lower (less than 4% of the total) when compared to the other pools and showed large spatial variability. We conclude that industrial forest plantations are a valuable tool to reduce atmospheric CO2 and mitigate climate change. Given the contribution of soils to total carbon stocks, special attention should be paid to forest management activities that affect the soil organic carbon pool.

This study has been monitored for five years by Sentinel-2 satellite images, at different seasons of the year, of the fluctuations in the water level of the Gallocanta Lake (between the provinces of Teruel and Zaragoza, Aragón, Spain) considered a hypersaline and endorheic wetland, which has characteristics that make it unique in the geographical area in which it is located, as well as for the operation of the system. Rainfall in the area has a wide variation giving the maximums in the months of May and June and the minimums in January and February. There are considerable fluctuations in the water level from the almost total drying of the lagoon to the filling with a depth of approximately 3 meters.

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

This research was conducted to analyze the content of Fe, Cu, Cd, Cr, and Pb in several species of fish taken from three lakes that is closely to disposal of industrial waste in Indonesia. The fish samples were taken from three lakes, namely, Muara Angke, Weda, and Morowali. The samples from Morowali were analyzed in April 2019, those from Weda from November to December 2019, and those from Muara Angke in June 2018. All the samples were then analyzed at the chemistry laboratory of the Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, and the Integrated Laboratory of IPB. The results showed that all types of fish from Morowali and Weda were no longer safe to consume because they contained Fe, Cu, Cd, and Cr exceeding the threshold of metal contamination. Meanwhile, all types of fish from Muara Angke, except for ayam-ayam, are still safe for consumption. The results of this study can be a source of information regarding metal content in fish and fish feed for safe consumption. Several studies have been done to determine the metal pollutants contained by fish. Given the high consumption rate of fish and the hazards of heavy metals on humans’ health, such research must be furthered

Circular Economy (CE) is a growing topic among scholars, industry and government aiming at decoupling economic growth and development from the consumption of finite resources. CE incorporates different meanings, from reduce, reuse and recycle activities to environmental degradation or resource scarcity, and supported by specific indicators to attain sustainable development. However, so far, there has been no agreement to measure how effective an industry/product is in making the transition from linear to circular approaches, particularly those affected the society. This research work aims to perform a systematic literature review (n=60) to analyze and discuss how social aspects have been considered and integrated in the CE research so far. Moreover, this review provides and overview of the literature on social impact within CE, that resulted in three main outputs: a knowledge map of the CE, an analysis of social aspects within CE, and the theories/frameworks used to evaluate social impact of CE. Finally, this study brings to light how CE implementation can affect society and highlights the importance of social dimension in the domains of CE and policy-making community, which could help moving CE towards a sustainable development.

Heavy metals pollution in the Straits of Malacca warrants the development of rapid, simple and sensitive assays. Enzyme-based assays are excellent preliminary screening tool with near real-time potential. The heavy-metal assay based on the protease ficin was optimized for mercury detection using Response Surface Methodology. The inhibitive assay is based on ficin action on the substrate casein and residual casein is determined using the Coomassie dye-binding assay. Heavy metals strongly inhibit the hydrolysis. A Central Composite Design (CCD) was utilized to optimize detection. The results show a marked improvement for the concentration causing 50% inhibition (IC50) for mercury, silver and copper. Compared to One-factor-at-a-time (OFAT) optimization, RSM gave an improvement of IC50 from 0.060 (95% CI, 0.0300.080) to 0.017 (95% CI, 0.0160.019), from 0.098 (95% CI, 0.0770.127) to 0.028 (95% CI, 0.0220.037) and from 0.040 (95% CI, 0.035.045) to 0.023 (95% CI, 0.0200.027), for mercury, silver and copper, respectively. A near real-time monitoring of mercury concentration in the Straits of Malacca at one location in Port Klang was carried out over a 4-h interval for a total of 24 h and validated by instrumental analysis with the result revealing an absence of mercury pollution in the sampling site.

Among others, road traffic, industrial emissions, commercial activities, smoking and cooking are considered as major contributing factors for the increasing levels of pollutants in atmosphere. High levels of potentially toxic metals and microbes in atmosphere, especially in indoor air, may pose serious threat to human health. Therefore, concentration and associated health risks of potentially toxic trace metals (Cd, Cr, Cu, Fe, Mn, Pb, and Zn) and their risk to human health, and microbial load in indoor air was assessed using air condition (AC) filter dust samples collected from 5 locations representing residential, agricultural and industrial settings of Eastern Province, Kingdom of Saudi Arabia. The levels of trace metals varied considerably among sampling areas, with the highest levels of Cr and Cd recorded in the Industrial-area sites followed by the Agricultural and Urban-Residential sites. The highest levels of Pb and Fe were found in the Agricultural area sites followed by the Industrial and Urban-Residential area sites. The metals in dust sample, especially Cd, Cr and Pb, showed a considerable health risk through dermal pathway. Among the sites, the highest hazard quotient for these metals was found for Al-Qatif-Industrial areas sites and among the metals it was the highest for Cd. The cancer risk from the metals contained in AC filter dust was negligible. Samples collected from Agricultural and Industrial area sites were substantially contaminated with bacteria and fungi, respectively. Bacterial contaminants were mostly Gram Negative, with considerable antibiotic resistance and haemolytic activity. Thus, indoor air quality as assessed by AC filter dust depicted that a considerable health risk could be posed by the trace heavy metals and microorganisms for a long-term exposure. Furthermore, this study demonstrated that AC filters dust could be a unique and reliable test sample for the assessment of indoor environment.

In the present work, we evaluate the prediction capability of six Pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (Ks). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were construct for Ks from clay percentage, bulk density and saturation water content data. The results show, for the evaluated models, that one model present an overestimation for Ks>0.5 cm h-1 values, three models have a underestimation for Ks>1.0 cm h-1 and two models have a good correlation (R2>0.98) but are necessary more than three parameters. Nevertheless, the last two models requires from three to four parameters in order to get the optimization. By other hand, the models proposed in this work have a similar correlation with a less number of parameters: the fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and a R2 = 0.9901 when we use two.

Water resources are threatened nowadays by pollution that comes from domestic, industrial and agricultural discharges without prior treatment. This pollution causes the degradation of water quality. Surface pollutants can seep through the soil into water tables. The objective of our work is to assess and control the physicochemical quality of the Chari Baguirmi groundwater, to protect human health. The quality of 83 boreholes was assessed, while performing analysis for 12 physicochemical parameters at the National Water Laboratory and at the Center for Quality Control of Foodstuffs in Chad. These parameters are: pH, EC, Ca2+, Mg2+, Na+, K+, Cl-, SO42-, NH4+ and NO3- , Fe2+ and HCO3-. Also, the results obtained were compared with WHO standards. The geochemical statistical approach has made it possible to characterize the hydro geochemical properties and to understand the major processes of the mineralization of groundwater resources in Chari Baguirmi region in Chad. Some of its waters are acidic and weakly mineralized, rich in Fe2+ and NH4+. The origin of the mineralization is due to the alteration of the host rocks and to the hydrolysis of silicate and ferromagnesian minerals as well as anthropogenic pollution. The ammonium concentrations in N’Djamena boreholes are higher than WHO standards, indicating the presence of pollution which may come from organic waste. These results constitute a preliminary step in understanding hydro geochemical functioning and a basis for monitoring the physicochemical quality of the water in the study area.

Bioenergy with carbon capture and sequestration (BECCS) is one strategy to remove CO2 from the atmosphere. To assess the potential scale and cost of CO2 sequestration from BECCS in the US, this analysis models carbon efficiencies and costs of biomass production, delivery, power generation, and CO2 capture and sequestration in saline formations. The analysis includes two biomass supply scenarios (near-term and long-term), two biomass logistics scenarios (conventional and pelletized), two generation technologies (pulverized combustion and integrated gasification combined cycle), and three cost accounting scenarios (gross cost, net cost after electricity revenues, and net cost after electricity revenues with avoided emissions from conventional power generation). Results show cost Mg-1 CO2 as a function of CO2 sequestered (simulating capture up to 90% of total CO2 sequestration potential) and associated spatial distribution of resources and generation locations for the array of scenario options. Under a near-term scenario using 222 million Mg yr-1 of biomass, up to 196 million Mg CO2 can be sequestered at scenario-average costs ranging from $60 to $158 Mg 1 CO2; under a long-term scenario using 823 million Mg yr-1 of biomass, up to 727 million Mg CO2 yr 1 can be sequestered at scenario-average costs ranging from $32 to $242 Mg-1 CO2. These costs are largely influenced by cost accounting scenario, and the CO2 sequestration potential may be reduced if future competing demand reduces resource availability. Results suggest there are multiple feedstock-logistics-generation pathways toward CO2 drawdown that could be incrementally trialed and monitored for environmental sustainability effects. Interactive visualization of results is available at [final link to be determined].

Abstract The COVID-19 pandemic has tremendously affected the African continent and the rest of the world. Most businesses have closed and a lot of people have lost their jobs. The aviation industry has been shaken to the core with airlines losing millions of dollars and flights being cancelled. The tourism industry has consequently been affected due to restricted travel of tourists, impacting wildlife conservation and livelihoods. Schools, colleges and universities have been closed. The virus has infected millions of people and hundreds of thousands of people have died globally putting strain on health systems especially those of hard hit countries. Various countries all over the world have put measures to control the spread of the virus through lockdowns and social distancing policies. The reduced economic activities and mobility of people has resulted in improved air quality, cleaner water and beaches in some countries. However there are also negative impacts such as challenges in waste management, increased pharmaceutical and household waste and discovery of the corona virus in wastewater, a potential threat to public health. A considerable amount of research has been done on the socio-economic impacts of COVID-19 in Africa but there is still limited research on its impact on the environment. This paper serves to highlight the observed and potential environmental impacts of COVID-19 in Africa.

Bacteria and archaea participate in and are influenced by processes of substance circulation and energy exchanges in natural environment. Generally, the community changes of bacteria and archaea in sediment are mainly driven by seasonality in mid-latitude regions. But in our study, water diversion to Fen river played a more important role on OTU number, diversity and community structure of bacteria and archaea in sediment than seasonal variation, which was found by 16S rRNA high-throughput sequencing technology. This phenomenon might be caused by external transferred water on the physicochemical water environment and accelerated release of positive nitrogen from sediment caused by rise of water level. Changes of carbon-nitrogen cycle and increase of electrical conductivity (EC) value induced more diversion-responders than season-responders both for bacteria and archaea. Seasonal changes have been influencing bacteria and archaea mildly throughout the whole study reach. After water diversion, the environment indicators relating to bacteria community obviously changed from nutrients to salinity while that for archaea almost disappeared. Our research showed the effects of human activities on the communities of bacteria and archaea outweigh the forcing from natural seasonal changes in mid-latitude regions and revealed the mechanism, highlighting different responses of bacteria and archaea to environmental changes.

In this study a method for predicting the preferred pleasantness induced by different forest environments, represented by virtual photographs, was proposed and evaluated using a novel Anti-Environmental Forest Experience Scale psychometric test. The evaluation questionnaire contained twenty-one items divided into four different subscales. The factor structure was assessed in two separate samples collected online (sample 1: N = 254, sample 2: N = 280). The internal validity of the four subscales was confirmed using an exploratory factor analysis. Discriminant validity was tested and confirmed using the Amoebic Self Scale (Spatial-Symbolic domain). Concurrent validity was confirmed using the Connectedness to Nature Scale. Predictive validity was based on assessment of pleasantness induced by nine different photographs (control – urban landscapes, forest landscapes, dense forest landscapes), with subscales differently correlated with the level of pleasantness assessed for each photograph. This evaluation instrument is appropriate for predicting preferred pleasantness induced by different forest environments.

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emissions inventory for this activity is a challenge today, mainly to perform modeling of air quality. There are free available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were the black carbon, the organic carbon, fine and coarse particulate matter, respectively. The inputs were pre-formatted to enter to the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source.

The European heatwave of 2018 led to record-breaking temperatures and extremely dry conditions in many parts of the continent resulting in widespread decrease in agricultural yield, early tree-leaf senescence, and increase in forest fires in Northern Europe. Our study aims to capture the impact of the 2018 European heatwave on terrestrial ecosystem through the lens of a high-resolution solar-induced fluorescence (SIF) data acquired from the Orbiting Carbon Observatory (OCO-2) satellite. SIF is proposed to be a direct proxy for gross primary productivity (GPP) and thus can be used to draw inferences about changes in photosynthetic activity in vegetation due to extreme events. We explore spatial and temporal SIF variation and anomaly during spring and summer months across different vegetation types (agriculture, broadleaved forest, coniferous forest, and mixed forest) during the European heatwave of 2018 and compare it to non-drought conditions (most of Southern Europe). About one-third of Europe’s land area experienced a consecutive spring and summer drought in 2018. Comparing 2018 to mean (2015-2017) conditions, we found a change in intra-spring season SIF dynamics for all vegetation types, with lower SIF during the start of spring followed by an increase in fluorescence from mid-April. Summer, however, showed a significant decrease in SIF. Our results show that particularly agricultural areas were severely affected by the hotter drought of 2018. Furthermore, the intense heat wave in Central Europe showed about 31% decrease in SIF values during July and August as compared to the mean over three previous years. Furthermore, our MODIS and OCO-2 comparative results indicate that especially for forests, OCO-2 SIF has a quicker response and possible higher sensitivity to drought in comparison to MODIS’s fPAR and NDVI when considering shorter reference periods, which highlights the added value of remotely sensed solar-induced fluorescence for studying the impact of drought on vegetation.

Gold nanoparticles, were deposited in titanium oxide (TiO2) Degussa-P25 with the Photodeposition method in the presence of UV light at different concentrations. It was determined by diffuse reflectance (DF), Scanning electron microscopy (SEM), that the Photodeposition method is effective for the inclusion of gold particles on the surface. The catalyst band gap showed a reduction to 2.9 e.V, as well as it was observed that the gold-doped catalyst shows absorption in the visible light range around 500 to 600 nm. The percentage of deposited gold nanoparticles was determined by energy dispersive spectroscopy (EDS). The experimental data were analyzed using different analytical techniques (UV-Vis spectrophotometry, TOC total organic carbon), with these results a carbon-based mass balance and reaction kinetics were generated using the Langmuir-Hinshelwood (LH-HW) heterogeneous catalysis model. For the estimation of the kinetic constants, the non-linear regression of the Levengerd Marquad algorithm was used, with these results, kinetic models of the degradation of the molecule and the generation and consumption of Organic Intermediate Products (OIP) were generated.

In the present study, a five-year follow-up was performed by remote sensing of the calcium carbonate precipitation in La Gitana karstic lake (located on the province of Cuenca, Spain). The important role that calcium carbonate precipitation plays in the ecology of the lake is well known for its influence on the vertical migrations of phytoplankton, the concentration of bioavailable phosphorus and, therefore, the eutrophication and quality of the waters. Whiting take place between the months of July and August, and it can be studied at this time through its optical properties, with the main objective of offering updated data on a phenomenon traditionally studied and establishing possible relationships between abiotic factors such as temperature and/or rainfall. The atmospheric temperature data collected by the meteorological station suggest a possible relationship between the appearance of the white phenomenon and a pulse of previous maximum temperatures. On the other hand, no apparent relationship was found between rainfall and water bleaching.

The Sustainable Development Goals (SDGs) purport to report holistically on progress towards sustainability and do so using more than 231 discrete indicators with a primary objective to achieve a balance between the environment, social and economic aspects of development. The research question underpinning the analyses presented in this paper is: are the indicators in the SDGs sufficient and fit-for-purpose to assess the trajectory of natural resources towards sustainability? We extracted the SDG indicators that monitor the state of natural resources, or alternately support policy or governance for their protection, and determined if these are adequate to provide the essential data on natural resources to achieve the aims of the SDGs. The indicators are clustered into four natural resource categories; land, water (both marine and freshwater), air and biodiversity. Indicators for monitoring land resources show that the most comprehensive land resource indicator, for degraded land, is not fully implemented and that missing from land monitoring is an evaluation of vegetation health outside of forests and mountains, the condition of soils, and most importantly the overall health of terrestrial ecosystems. Indicators for monitoring water resources have substantial gaps, unable to properly monitor water quality, water stress, many aspects of marine resources and most significantly, the health of fresh and salt water ecosystems. Indicators for monitoring of air have recently become more comprehensive, but linkage to IPCC results would benefit both programmes. Monitoring of biodiversity is perhaps the greatest weakness of the SDG Agenda, having no comprehensive assessment even though narrow aspects are monitored. Again, deliberate linkages to other global biodiversity programmes (e.g. CBD and the Post 2020 Biodiversity Framework; IPBES; Living Planet, etc.) are recommended on condition that data can be defined at a country level. While the SDG list of indicators in support of natural resource is moderately comprehensive, it lacks holistic monitoring in relation to evaluation of ecosystems and biodiversity to the extent that these missing but vital measures of sustainability threaten the entire SDG Agenda. In addition, an emerging issue is that even where there are appropriate indicators, the amount of country-level data remains inadequate to fully evaluate sustainability. This signals the delicate balance between the extent and complexity of the SDG Agenda and uptake at a country level

Air pollution has become the world’s single biggest environmental health risk of the past decade, causing about 7 million yearly deaths worldwide. One of the dominant air pollutants is fine particulate matter (PM2.5), a product of combustion. Exposure to PM2.5 has been associated with decreased lung function, impaired immunity, and exacerbations of lung disease. Accumulating evidence suggests that many of the adverse health effects of PM2.5 exposure are associated with lung inflammation and oxidative stress. While the physical structure and surface chemistry of PM2.5 are surrogate measures of particle oxidative potential, little is known about their contributions to negative health effects. In this study, we used functionalized carbon black particles as surrogates for atmospherically aged combustion formed soot to assess the effects of PM2.5 surface chemistry in lung cells. We exposed the BEAS-2B lung epithelial cell line to different soot at a range of concentrations, and assessed cell viability, inflammation, and oxidative stress. Our results indicate that exposure to soot with varying particle surface composition results in differential cell viability rates, expression of pro-inflammatory and oxidative stress genes, and protein carbonylation. We conclude that particle surface chemistry, specifically oxygen content, in soot modulates lung cell inflammatory and oxidative stress responses.

Mitigation of global warming requires an understanding of where energy is produced and consumed, the magnitude of carbon dioxide generation, and proper understanding of the Carbon Cycle. The latter leads to the distinction between and need for both CO2 and biomass CARBON sequestration. Short reviews are provided for prior technologies proposed for reducing CO2 emissions from fossil fuels or substituting renewable energy, focusing on their limitations. None offer a complete solution. Of these, CO2 sequestration is poised to have the largest impact. We know how to do it. It will just cost money, and scale-up is a huge challenge. Few projects have been brought forward to semi-commercial scale. Transportation accounts for only about 30% of U.S. overall energy demand. Biofuels penetration remains small, and thus, they contribute a trivial amount of overall CO2 reduction, even though 40% of U.S. corn and 30% of soybeans are devoted to their production. Bioethanol is traced through its Carbon Cycle and shown to be both energy inefficient, and an inefficient use of biomass carbon. Both biofuels and CO2 sequestration reduce FUTURE CO2 emissions from continued use of fossil fuels. They will not remove CO2 ALREADY in the atmosphere. The only way to do that is to break the Carbon Cycle by growing biomass from atmospheric CO2 and sequestering biomass CARBON. Theoretically, sequestration of only a fraction of the world’s tree leaves, which are renewed every year, can get the world to Net Zero CO2 without disturbing the underlying forests. Thoughts are put forth on how to achieve secure permanent biomass sequestration.

Urbanization has impacted biodiversity and ecosystems at a global scale. At the same time, it has been recognized as a driver of the gap between humans and nature. The lack of direct contact with nature can deteriorate several aspects of human wellbeing, and change knowledge and attitudes of people towards the environment. However, this phenomenon is still poorly understood in Megacities outside developed countries. Here, we explore the relationship between ecological knowledge and self-reported wellbeing in an important urban park in Santiago, Chile. We conducted semi-structured surveys to park users to explore their notions, preferences, ecological knowledge of plants and birds and self-reported wellbeing. Citizens associated urban parks mainly with “nature”, and particularly with the presence of trees and plants. Trees were recognized as the most relevant elements of urban parks, in turn, birds were ranked as the less relevant. Regarding ecological knowledge, respondents correctly identified an average of 2.01 plants and 2.44 birds out of a total of 10 for each taxon, and exotic species were more likely to be recognized. Park users also reported high scores for self-reported wellbeing. Interestingly, variance of self-reported wellbeing scores tended to increase at low levels of ecological knowledge of trees, but no significant relationship was detected with knowledge of birds, nor native species. These results suggest that parks can positively contribute to bring people closer to nature. Ecological knowledge was related to self-reported wellbeing. Improving ecological knowledge can be critical to restore the relationship between humans and nature in megacities.

Rapidly and repeatedly ascertaining the health status of coral reefs is an ever more pressing issue as part of activities to understand and monitor the damaging impacts of climate change. A combination of increasing ocean temperatures, acidity and frequency of extreme storm events continues to alter the marine environment beyond what sensitive organisms, such as coral, can cope with. It is therefore vital to establish technologies and validated methods to provide a metric or indication into the health of these organisms. There are currently many surveys and techniques used by coral scientists to uncover insights into the status and assessment of coral reefs, from colour wheels to multispectral satellite surveys. Here we outline an array of current techniques and methods focused specifically on coral monitoring and health diagnosis, ranging across the length scales from simple diver-based surveyance to satellite remote sensing. The technique of using hyperspectral fluorescence imaging is also introduced as a viable novel addition to aid and extend the current toolbox of available technologies.

The paper presents a modeling framework to analyze the effect of episodic rainfall supply on groundwater dynamics in the Ionian coastal plain multilayered aquifer. The focus is essentially on the short-term behavior of the shallowest layer, with a specific analysis on episodic rainfall events. In the studied aquifer, groundwater level responds sensitively to rainfall events, highlighting the presence of preferential recharge zones. The hydraulic head peak is a function of groundwater level antecedent to the rainfall event. A kinematic dispersion wave model was used to model infiltration processes via preferential pathways. A one-dimensional and non-linear particle based numerical model was developed. Particles with constant water volume travel according to celerity and hydraulic dispersion to simulate the infiltration rate wave through the vadose zone. The flow rate that reaches the water table represents the input function to determine groundwater level fluctuations along groundwater flow direction and according to the lithological features of the surficial levels of the multilayered aquifer, its storage capacity changes passing from unconfined to confined conditions. The model was validated with high time resolution time series of precipitation and groundwater level coming from Terra Montonata meteo-climatic and groundwater level monitoring station. The developed model represents a basis for evaluating and predicting groundwater discharge of the shallowest layers of the Ionian coastal multilayered aquifer under natural conditions including episodic rainfall.

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (?-ω) model, can suffer from significant errors over croplands (in average between -9.4K and + 12.0K for Single Channel Algorithm SCA; -8K and + 9.7K for Dual-Channel Algorithm DCA) if the vegetation scattering albedo (omega) is treated as a constant and the temporal variations are not accounted. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer ?-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). The validation was performed from 14 May to 13 December 2015 over 61 Climate Reference Network sites (SCRN) classified as croplands. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics on croplands are better represented by a time-dynamic single scattering albedo.

Wetlands are carriers of metals and organic pollutants from natural and anthropogenic sources. Studies have shown that sediments are sinks for these pollutants as they carry more than 99% of the total amount of metals which are released as soluble metals into the Lagoon. The University of Lagos, located at Akoka North eastern part of Yaba in Lagos Mainland runs along a highly industrialized and residential area. This paper reports the total metal concentrations in wetland and sediment and their seasonal variations. Wetland and sediment samples were collected for two seasons in 8 sampling sites. Results showed wetland data having lower concentrations of metals as compared to sediments. Wet season had higher concentrations of metals as compared to other season. Total concentrations in wetlands were Cd (1.0-6.0), Cu (1.0-11.0), Cr (0.3-82.7), Zn (2.7-65.0) and Pb (0.3-16.0) all in μg L-1 respectively. Statistical analysis showed that there was a significant difference between the wet and dry seasons for sediments. Cd was the only metal at acceptable levels while Cr, Cu, Pb and Zn concentrations all exceeded levels deemed acceptable by the SABS and the EPA. Therefore, the wetland is in poor health.

This study investigated the spatial variability of soil organic carbon (SOC), total nitrogen (TN), soil microbial biomass carbon (SMBC) and soil microbial biomass nitrogen (SMBN) in Hongqipao reservoir dominated by different vegetation types and the possible relationships with other soil properties. Top 0–50cm soil samples were collected in sites dominated by different vegetation types within the reservoir littoral zone. There was high spatial variability for SOC, TN, SMBC and SMBN in the Hongqipao reservoir. In addition, the SOC, TN, SMBC and SMBN contents decreased with increasing soil depth. This could be attributed by the fact that when plants detritus decompose, most of their organic matter is mineralized and a new soil layer which contains a greater amount of organic carbon is formed at the top. According to Pearson's correlation values and redundancy analysis (RDA) results, SOC was significantly and positively correlated with TN likely because the vegetation organic matter and liter could be the main nitrogen sources. Similarly, soil moisture content (MC) was significant positive correlated with SOC and TN. Conversely, BD was significant negative correlated with SOC and TN contents in the 0-50 cm soil profiles. However, no significant correlations were observed between SOC, TN, SMBC and SMBN contents and soil pH values. SMBN was significantly and positive correlated with C:N ratio and BD and negative related with MC. Multiple linear regression model revealed that all measures soil properties in this study could explain higher significant variability of the response variables (SOC, TN, SMBC and SMBN contents). This implies that all the measured soil variables within the different vegetation types in the reservoir played a crucial role in determining the contents of SOC, TN, SMBC and SMBN. This study further suggests that vegetation types play a major role in determining the spatial characteristics of SOC and TN. Any changes in the vegetation types in the reservoir may influence the distribution of SOC and TN. This may affect the global carbon budget and the atmospheric greenhouse gas concentration significantly.

Mangrove forests store and sequester large area-specific quantities of blue carbon (C_org). Except for tundra and peatlands, mangroves store more C_org per unit area than any other ecosystem. Mean mangrove C_org stock is 738.9 Mg C_org ha⁻¹ and mean global stock is 6.17 Pg C_org, which equates to only 0.4–7% of terrestrial ecosystem C_org stocks but 17% of total tropical marine C_org stocks. Seagrasses sequester more C_org per unit area than mangroves (179.6 g C_org m⁻²·a⁻¹) but twice the C_org sequestered by mangroves globally (15 Tg C_org a⁻¹). Mangroves sequester only 4% (range 1.3–8%) of C_org sequestered by terrestrial ecosystems, indicating that mangroves are a minor contributor to global C storage and sequestration. CO₂ emissions from mangrove losses equate to 0.036 Pg CO₂-equivalents a⁻¹ based on rates of C sequestration but 0.088 Pg CO₂-equivalents a⁻¹ based on complete destruction for conversion to aquaculture and agriculture. Mangrove CO₂ emissions account for only 0.2% of total global CO₂ emissions but 18% of CO₂ emissions from the tropical coastal ocean. Despite significant data limitations, the role of mangrove ecosystems in climate change mitigation is globally insignificant but may be more significant and effective at the national and regional scale.

The most massive and fast-eroding thaw slump of the Northern Hemisphere located in the Yana uplands of northern Yakutia was investigated to assess in detail the cryogenic inventory and carbon pools of two distinctive Ice Complex stratigraphic units and the uppermost cover deposits. Differentiating into modern and Holocene near-surface layers (active layer and shielding layer), highest total carbon contents were found in the active layer (18.7 kg m-2), while the shielding layer yielded much lower carbon content of 1.8 kg m-2. The late Pleistocene upper Ice Complex contained 10.4 kg m-2 total carbon, and the mid-Pleistocene lower Ice Complex 17.7 kg m-2. The proportion of organic carbon from total carbon content is well above 70% in all studied units with 94 % in the active layer, 73% in the shielding layer, 83% in the upper Ice Complex and 79% in the lower Ice Complex. Inorganic carbon is low in the overall structure of the deposits.

Sentinel-2 provides the opportunity to map the snow cover at unprecedented spatial and temporal resolution at global scale. Here we calibrate and evaluate a simple empirical function to estimate the fractional snow cover (FSC) in open terrain using the normalized difference snow index (NDSI) from 20 m resolution Sentinel-2 images. The NDSI is computed from flat surface reflectances after masking cloud and snow-free areas. The NDSI-FSC function is calibrated using Pléiades very high resolution images and evaluated using independent datasets including SPOT 6/7 satellite images, time lapse camera photographs, terrestrial lidar scans and crowd-sourced in situ measurements. The calibration results show that the FSC can be represented with a sigmoid-shaped function 0.5×tanh(a×NDSI+b)+0.5 where a = 2.65 and b = -1.42 yielding a root mean square error of 25%. Similar RMSE are obtained with different evaluation datasets with a high topographic variability. With this function, we estimate that the confidence interval on the FSC retrievals is 38% at the 95% confidence level.

The presence of heavy metals in cocoa crops is currently a serious problem for farmers and producers in various regions of Peru. Exports of cocoa and its derivatives to European markets are threatened by possible indications of contamination of heavy metals such as Cadmium (Cd) in cocoa beans for export, some at levels higher than those allowed by food regulations established by European Community, which are oriented to consumer protection. The possible sources of cadmium contamination in cocoa crops can be due to natural activities, such as volcanic activities, erosion processes and sedimentation in rocks that contain minerals with a high content of heavy metals (Greenockite, Burnsite, Hawleite, among others), and by anthropogenic activities such as: mining of associated deposits, agriculture (use of fertilizers), smelting of minerals and burning of fossil fuels. Currently, there is no information about contents of heavy metals in areas located in The Campo Verde-Honoria-Tournavista corridor (Ucayali Region and Huanuco Region), due to this, in this work we make a study of this region. A methodology will be used to take cocoa samples from the seed and soil in these areas, and then through chemical analysis, determine the concentrations of heavy metals, using an atomic absorption spectrophotometer. As a consequence of this study, we determined and concluded that the concentrations of cadmium obtained in soils are slightly higher than European standards allowed. Therefore, with this information we prepare a geochemical cadmium map in soils for the study area, which will help cocoa producers to identify areas that exceed the allowed cadmium values, in order to comply with standards that European Community demands in relation of concentration levels of heavy metals (Cadmium) in chocolate. In this way, we can carry out in the future a mitigation plan for areas with cadmium problems, which allows to reduce their content in order to export the product without any problem. .

The paper presents a conceptual model of the route of macroplastic debris (5 > mm) through a fluvial system, which can support future works on the overlooked processes of macroplastic storage and remobilization in rivers. We divided the macroplastic route into (1) input, (2) transport, (3) storage, (4) remobilization and (5) output phases. Phase 1 is mainly controlled by humans, phases 2–4 by fluvial processes, and phase 5 by both types of controls. We hypothesize that natural characteristics of fluvial systems and their modification by dam reservoirs and flood embankments construction are key controls on macroplastic storage and remobilization in rivers. The zone of macroplastic storage can be defined as a river floodplain inundated since the beginning of widespread disposal of plastic waste to the environment in the 1960s and remobilization zone as a part of the storage zone influenced by floodwaters and bank erosion. The amount of macroplastic in both zones can be estimated using data on the abundance of surface- and subsurface-stored macroplastic and the lateral and vertical extent of the zones. Our model creates the framework for estimation of how much plastic has accumulated in rivers and will be present in future riverscapes.