The biomass fraction of processed municipal and industrial wastes added to soil can maintain, and in some case improve, the soil’s organic fertility. One of the main constraints in the agricultural use of the sewage sludge is its content of heavy metals. In the long term, soil administration of sewage sludge in agriculture could result in a risk of environmental impact. The aim of this research was to evaluate the effects of medium-term fertilization with sewage sludge diversely processed on the soil’s organic carbon content and humification – mineralization soil’s processes and on the physical and mechanical properties of soil. Furthermore, the heavy metals accumulation in soil, in their total and available form, has been investigated. After eight years of administration to soil, the use of sewage sludge as an agricultural soil amendment has contributed to maintaining the soil’s organic fertility. An increase in concentrations of total Ni and Zn was detected in soil. For bioavailable form (DTPA-extractable) this trend was evidenced for all heavy metals analysed. However, the concentrations of total and available heavy metals in the soil did not exceed the legal threshold established by Italian law for unpolluted soils.

The purpose of the present research was to analyze the available data on river restoration projects. As the framework of our study, we conducted a structured international survey. We asked selected entities and experts from among those responsible for river restoration in European countries about the details and costs of European Union river restoration projects. We examined 119 river restoration projects that were implemented in Europe between 1989 and 2016; some of the projects were still ongoing. We observed that the number of river restoration projects has been increasing since 1989, which expresses society’s growing interest in improving the quality of aquatic environments. We revealed that 56% of these European river restoration projects have been implemented by dedicated entities and stakeholders, not as part of any structured, larger-scale river restoration policy; this indicates that most European countries do not have integrated plans for river restoration. Our analysis showed that 52% of the projects analyzed have been designed and implemented without the participation of local stakeholders. It also showed that the budgets for river restoration projects did not differ significantly across various time horizons from 1981 to 2016. In our study, the average cost of restoring 1 ha of an average European river was 310 000 EUR (or 195 000 EUR if 4 outlying values are excluded). Considering these projects’ permanent assets and including their amortization, for European river systems, we calculated the average unit price of a river restoration’s value in terms of ecosystem meta-service to be 7 757 EUR · ha^-1 · year^-1 (4 875 EUR · ha^-1 · year^-1 if 4 outlying values were excluded).

The air in subterranean karst cavities is often depleted in methane (CH₄) relative to the atmosphere. Karst is considered a potential sink for the atmospheric greenhouse gas CH₄ because its subsurface drainage networks and solution-enlarged fractures facilitate atmospheric exchange. Karst landscapes cover about 14% of earth’s continental surface, but observations of CH₄ concentrations in cave air are limited to localized studies in Gibraltar, Spain, Indiana (USA), Vietnam, Australia, and by incomplete isotopic data. To test if karst is acting as a global CH₄ sink, we measured the CH₄ concentrations, δ¹³C_CH4, and δ²H_CH4 values of cave air from 33 caves in the USA and three caves in New Zealand. We also measured CO₂ concentrations, δ¹³C_CO2, and radon (Rn) concentrations to support CH₄ data interpretation by assessing cave air residence times and mixing processes. Among these caves, 35 exhibited subatmospheric CH₄ concentrations in at least one location compared to their local atmospheric backgrounds. CH₄ concentrations, δ¹³C_CH4, and δ²H_CH4 values suggest that microbial methanotrophy within caves is the primary CH₄ consumption mechanism. Only 5 locations from 3 caves showed elevated CH₄ concentrations compared to the atmospheric background and could be ascribed to local CH₄ sources from sewage and outgassing swamp water. Several associated δ¹³C_CH4 and δ²H_CH4 values point to carbonate reduction and acetate fermentation as biochemical pathways of limited methanogenesis in karst environments and suggest that these pathways occur in the environment over large spatial scales. Our data show that karst environments function as a global CH₄ sink.

This paper aims to investigate carbon monoxide (CO) concentrations on roadways of Karachi, potential blood levels carboxy-hemoglobin (COHb) in Karachi. Geographical information system (GIS) was used for spatial analysis of diseases potentiality while an interpolation technique has been applied for surface generation with town boundaries and later evaluates risk areas.The higher concentration of carbon monoxide in the ambient is mainly due to automobile emissions. The City center and CBD areas are more perilous.

One source of kaolinite-rich wastes is from mine tailings and the generation of enormous volumes of mine tailings waste is standard practice in this industry. These volumes of waste are, at present, dumped, provoking significant environmental impact and transforming the environment. The impact of storing coal waste requires the study of eco-innovative solutions for the assessment of waste types. The present investigation has the objective of expanding the knowledge on the behavior of new siliceous-aluminum minerals with pozzolanic activity, of added value in the manufacture of similar cements. Four samples were characterized to determine their chemical, morphological and mineralogical composition. The samples were subjected to different thermal activation conditions for the transformation of an inert waste into a material with cementitious properties. XRD analysis have confirmed the total transformation of kaolinite into metakaolinite. The results have shown that after the activation process, the coal refuse presented good pozzolanic activity, meaning that it may be used as a pozzolanic addition in industrial cements, thereby removing high levels of contaminated waste from the environment. In subsequent investigations, research work will continue with the replication of cements with this pozzolanic addition for use in the manufacture of sleepers and slab track railway system.

This paper addresses the atmospheric emissions from oil and gas extraction and production in Greece. The study was carried out in 2014 in the Kavala gulf, which currently is the only location of oil and gas production in Greece and where the exploration activities for hydrocarbons started in the late ‘60’s. This study presents the qualitative and quantitative characteristics of atmospheric emissions, in relation also to the emissions’ control management system. Particular reference is made to sulphur compounds since the existence of volcanic rocks results to increased amounts of H₂S. The results shows that, currently, atmospheric emissions of pollutants during extraction and production of hydrocarbons in Greece are very low and do not have any significant effect on air quality and climate change. Since it is expected that exploitation of hydrocarbons and oil and gas extraction and production will increase in the future, appropriate measures should be taken to ensure environmental protection, such as the development of integrated monitoring systems and the use of up to date emission control technologies.

Data dealing with the assessment of heavy metal pollution in road dusts in Jeddah, Saudi Arabia and its implication to human health risk of human exposure to heavy metals, are scarce. Road dusts were collected from five different functional areas (traffic areas TA, parking areas PA, residential areas RA, mixed residential commercial areas MCRA and suburban areas SA) in Jeddah and one in rural area (RUA) in Hada Al Sham. We aimed to measure the pollution levels of heavy metals and estimate their health risk of human exposure applying risk assessment models described by USEPA. Using geo-accumulation index (I_geo), the pollution level of heavy metals in urban road dusts was in the following order Cd > As > Pb > Zn > Cu > Ni > Cr > V > Mn > Co > Fe. Urban road dust was found to be moderately to heavily contaminated with As, Pb and Zn, and heavily to extremely contaminated with Cd. Calculation of enrichment factor (EF) revealed that heavy metals in TA had the highest values compared to that of the other functional areas. Cd, As, Pb, Zn and Cu were severely enriched, while Mn, V, Co, Ni and Cr were moderately enriched. Fe was consider as a natural element and consequently excluded. The concentrations of heavy metals in road dusts of functional areas were in the following order: TA > PA > MCRA > SA > RA > RUA. The study revealed that both children and adults in all studied areas having health quotient (HQ) < 1 are at negligible non-carcinogenic risk. The only exception was for children exposed to As in TA. They had an ingestion health quotient (HQ_ing) 1.18 and a health index (HI) 1.19. The most prominent exposure route was ingestion. The cancer risk for children and adults from exposure to Pb, Cd, Co, Ni, and Cr was found to be negligible (< 1 x 10^-6).

Plants are an important feature of urban ecosystems which provide numerous environmental and ecosystem benefits such as defenses against noise and air pollution and conservation of biodiversity. The aim of this study was to investigate the structure and composition of urban vegetation in different urban habitats like roadsides, parks, gardens and playgrounds in Dhaka South City area. Stratified random sampling method was used in this study. A total of 221 plant species belonging to 63 families were identified and recorded. Among all plant species Swietenia macrophylla, Polyalthia longifolia, Cocos nucifera, Samanea saman, and Artocarpus heterophyllus are recorded as the most dominant. Most of the tree and shrub population were found between 6-9 m and 1-3m height classes whereas most of tree and shrub population were found in between 10-15cm dbh classes. Highest IVI was found for Swietenia macrophylla (193.22%) followed by Polyalthia longifolia (184.59%), Samanea saman (138.37%), Cocos nucifera (79.9%) and Delonix regia (68.27%) respectively. Average frequency, density, dbh and basal area were found 46.82%, 138.28 tree ha^-1, 458.59 cm ha^-1 and 12.33 m² ha^-1 respectively. Findings of this study reveals that structural attributes of plant represent quite young and still developing vegetation. This research will help to plan for future green infrastructure which will maintain ecosystem function, therefore, providing longer term benefits for the city dwellers.

Rapid urbanization has changed the structure and function of natural ecosystems, especially the floodplain ecosystems in SE Asia. This paper describes the ecological structure of vegetation stands and the usefulness of satellite images to characterize a disturbed tropical urban forest located in the lower floodplain of the Chao Phraya River, Thailand. Nine representative plots were established in Bang Kachao peninsula in 4 tropical urban forest types: rehabilitation forest, home-garden agroforestry, mangrove and park. The correlation between NDVI and LAI obtained from satellite images and plant structure from field surveys were analyzed. The NDVI had the highest relationship with stand factors for the number of families, number of species, Shannon-Weiner’s diversity index and total basal area. The LAI had the highest correlation with total basal area, number of canopy layers, stand density and canopy density. Linear regression predicted the correlation between NDVI and LAI with stand factors as show above. The trend in NDVI and LAI reflected the urban forest type, being high in rehabilitation and mangrove forests, moderate in home-gardens and low in parks. Future urban planning of the Bang Kachao peninsula should focus on rehabilitation to increase the biodiversity and complexity of the urban forest.

A large-scale, high-resolution, fully coupled hydrological/reservoir/hydroelectricity model is used to investigate the impacts of climate change on hydroelectricity generation and hydropower potential of non-powered dams across the Northeast United States megaregion with 11,037 dams and 375 hydroelectric power plants. The model is calibrated and validated using the U.S. Department of Energy records. Annual hydroelectricity generation in the region is 41 Terawatt-hours (Twh). Our estimate of the hydropower potential of non-powered dams adds up to 350 Twh. West Virginia, Virginia, Pennsylvania, and New York have significant potential for generating more hydroelectricity from already existing dams. On the other hand, this potential virtually does not exist for Rhode Island and Delaware and is small for New Jersey and Vermont. Climate change may reduce annual hydropower potential from non-powered dams by up to 13% and reduce current annual hydroelectricity generation by up to 8% annually. Increased rainfall in winters and earlier snowmelt in springs result in an increase in regional water availability in December through March. In other months, reduced precipitation and increased potential evapotranspiration rates combined with reduced recharge from the shift in spring snowmelt and smaller snowpack result in a decrease in availability of water and thus hydroelectricity generation. This changes call for the recalibration of dam operations and may raise conflict of interests in multipurpose dams.

The utilization for water resource has been of great concern to human life. To assess the natural water system in Kangding County, the integrated methods of hydrochemcial analysis, multivariate statistics and geochemical modelling were conducted on surface water, groundwater and thermal water samples. Surface water and groundwater were dominated by Ca-HCO₃ type, while thermal water belonged to Ca-HCO₃ and Na-Cl type. The analyzing results concluded the driving factors that affect hydrochemical components. Following the results of the combined assessments, hydrochemcial process was controlled by the dissolution of carbonate and silicate minerals with slight influence from anthropogenic activity. The mixing model of groundwater and thermal water was calculated using silica-enthalpy method, yielding cold-water fraction of 0.56-0.79 and estimated reservoir temperature of 130-199 ^oC, respectively. δD and δ¹⁸O isotopes suggested surface water, groundwater and thermal springs were of meteoric origin. Thermal water should have deep circulation through the Xianshuihe fault zone, while groundwater flows through secondary fractures where it recharges with thermal water. Those analytical results were used to construct a hydrological conceptual model, providing a better understanding of the natural water system in Kangding County.

This study presents results of the sediment yield Watershed of Ribeirão do Pinhal, in the city of Limeira, São Paulo, conducted under three different scenarios of the land use: 1 – land use in 2008, 2 – with reforested protection areas, 3 – the increase sugarcane's areas over grassland and citrus areas. The Soil and Water Assessment Tool (SWAT) was used as a hydro-sedimentological modeling tool to simulate these scenarios. This watershed was divided into five sub-watersheds according to the prevalent use, and adjustments were made in soils database parameters and cultures that are in SWAT, to adapt it to the Brazilian reality. Was used climatological data of eight years (2007-2014) for this modeling. Different sediment yield could be noted in the different types of land use, sub-watersheds and scenarios. The uses that presented higher sediment yield, in ascending order, were: natural vegetation, sugarcane, citrus, annual crop e grassland. Sub-watershed number 2 had the highest sediment yield (~10Mg.ha^-1), while the sub-watershed 5, the lowest (5.51Mg.ha^-1). This remained in the three scenarios. Overall, scenario 2 had the lowest sediment yield (7.74Mg.ha^-1). Scenario 1 had 8.37 Mg.ha^-1 and scenario 3, 8.58Mg.ha^-1. SWAT was considered efficient to simulate the sediment yield by scenarios and by use, combining different thematic and tabular data when performing the necessary adjustments on their original database.

We aimed at analyzing Chlorophyll-a and CDOM dynamics from field measurements and at assessing the potential of multispectral satellite data for retrieving water-quality parameters in three small surface reservoirs in the Brazilian semiarid region. More specifically, this work comprises i) analysis of Chl-a and trophic dynamics; ii) characterization of CDOM; iii) estimation of Chl-a and CDOM from OLI/Landsat-8 and RapidEye imagery. The monitoring lasted 20 months within a multi-year drought, which contributed to water-quality deterioration. Chl-a and trophic state analysis showed a highly eutrophic status for the perennial reservoir during the entire study period, while the non-perennial reservoirs ranged from oligotrophic to eutrophic, with changes associated with the first events of the rainy season. CDOM characterization suggests that the perennial reservoir is mostly influenced by autochthonous sources, while allochthonous sources dominate the non-perennial ones. Spectral-group classification assigned the perennial as CDOM-moderate and highly eutrophic reservoir, whereas the non-perennial ones were assigned as CDOM-rich and oligotrophic-dystrophic reservoirs. The remote sensing initiative was partially successful: the Chl-a was best modelled using RapidEye for the perennial; whereas CDOM performed best with Landsat-8 for non-perennial reservoirs. This investigation showed high potential for retrieving water quality parameters in dry areas with small reservoirs.

Solar radiation is the main energy source for mankind and an accurate data of solar radiation levels for a particular location is vital for the optimum operation of solar energy transducers such as photovoltaic cells and solar thermal collectors. In this work, we show that there is a linear relationship between recorded monthly average temperatures and solar radiation in Swaziland. The correlation can be utilized to develop two mathematical models for the estimation of solar radiation: one from the measured monthly average temperatures and the other based on the square-root of the difference between measured maximum and minimum monthly average temperatures. Both models fit the data well and can be applied to estimate solar radiation in other parts of the region.

Stara Planina is known for numerous occurrences and deposits of uranium and associated radionuclides. It is also famous for its geodiversity. The geologic framework is highly complex. The mountain is situated between the latitudes of 43° and 44° N and the longitudes from 22°16′ to 23°00′ E. Uranium exploration and radioactivity testing on Stara Planina began back in 1948. Uranium has also been mined in the zone of Kalna, within the Janja granite intrusive. The naturally-radioactive geologic units of Stara Planina are presented in detail in the paper.

The purpose of this paper was to analyze the development trend of hazardous chemical packaging towards low carbon economy from both qualitative and quantitative perspectives. Four types of relatively small volume packaging with volume/weight less than 450L/400kg, respectively, and three intermediate bulk containers (IBCs), which are widely used for hazardous chemicals were studied to calculate the carbon footprint (CF) from cradle to grave using life cycle assessment (LCA) method and to predict the future carbon emission of hazardous chemical packaging in the next five years (2016-2020), based on the export data of Tianjin Port in China. Grey model (GM) was adopted in the prediction. The results showed that majority of IBCs have lower carbon footprint than other types when the packaging contained same amount of same hazardous chemical. With the development of international trading, the demand of hazardous chemicals will increase as well. As the result, carbon emission generated by hazardous chemical packaging will increase accordingly. However, based on GM simulation result, increasing the amount of IBC use will effectively reduce the relative amount of carbon emission.

Mining for resources extraction may lead to several geological and associated environmental changes due to ground movements, collision with mining cavities and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e. subsidence, and degradation of vegetation health. Thus, monitoring short-term landscape dynamics in a reclaimed mine area may provide important information on the long-term geological and environmental impacts of mining activities. We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyse land-use and land-cover dynamics and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation health using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within the four years with 87.2% of growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that 66.5% of the vegetation of the study area was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide.

Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3 in the some of subbasin Hamedan Province West of Iran. The analysis of the rainfall indices are: simple rainfall intensity, very heavy rainfall days, maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. The final results show that each of rainfall indices differs in stations under the three GCMs model (GIAOM, MIHR, MPEH5) and emission scenarios A1B and B1, and RCP2.5, RCP8.5 scenarios. Relative change of daily intensity index varies from -9.93% - 25%, very heavy rainfall days 20.71% - 25.9% and yearly rainfall depth -15.71% - 13% can be observed at study area in 50y for future periods (2046–2065). Rainfall indices of sum wet days, nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days, simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6.

We apply principles of Gibbs phase plane chemistry to and across the entire ocean-atmospheric interface. Surface tension increments support a two dimensional, tangential pressure well known to determine rates of bulk gas, bubble, salt, spray and momentum transfer plus both sensible and latent heat fluxes. Hence it is worth asking whether tension mapping follows from current understanding of two dimensional composition. A history is provided dating back centuries and demonstrating that detrital organic macromolecules are central; subtle surfactant functional variation creates a microforcing field which dissipates turbulent energy at the sub-meter scale. Since we have just distributed major biopolymeric classes emitted as primary organic aerosol, further climate links can be established by considering full planar thermochemistry. Organic microlayer behaviors are reviewed with attention to confined, analog phase transitions among two dimensional “solid, liquid, (and) gaseous” states serving as elasticity indicators. We also discuss surfactant properties of general marine dissolved organic carbon, demonstrating that only proteins and lipids are capable of occupying significant local micro-area. The literature often suggests albumin and stearic acid as best proxies, and so we distribute their concentrations through multilevel global ecodynamic simulations. Consensus distributions are obtained in order to control adsorptive equilibria. Working from conservation of planar free energy, a parametric equation of state is devised relating excess coverage to the surface pressure-modulus. Constant settings for the proxy pair are drawn from laboratory study, and they successfully reproduce frequencies for surfactant solid-to-gas occurrence in ambient compression experiments. Functionally resolved organic measurements are rare and so we group them into super-ecological province tables showing that our bulk concentration estimates are reasonable. Outputs are then fed into a coverage-tension-elasticity code. Resulting contours traverse the critical range for piston velocity, bubble-spray and damping effects on either a regional or seasonal basis. There is also a possibility for widespread microlayer crystallization in polar seas. The concepts are a direct extension of our organic aerosol work, and the two approaches could be inserted into Earth System Models in tandem. Uncertainties in the logic are enumerated and include kinetic and thermochemical factors at multiple scales. But the problems are reducible through molecular modeling coupled to renewed laboratory and field study. Connections to marine colloids-gels, microlayer iron chelation, and linings of the ice channel network are discussed additionally.

In this study, we evaluated chlorophyll fluorescence (CF) under two extreme illumination conditions at plant scale with a passive spectroradiometer. Fluorescence (F) was estimated by reading directly from radiance spectra of a variety of plants illuminated with light-emitting diode (LED) grow lights in the laboratory. Solar-induced fluorescence (SIF) was estimated from spectral measurements of the same plants under sunlight using the Fraunhofer Line Depth (FLD) method. Chlorophyll fluorescence yield (F_yield) and solar-induced fluorescence yield (SIF_yield) were calculated by normalizing F and SIF with absorbed photosynthetically active radiation (APAR). Two approaches to estimating APAR were compared: utilizing white reference spectra and reflected spectra versus white reference spectra combined with the fraction of absorbed photosynthetically active radiation (fPAR) derived from literature. Average F and SIF were different by a factor of approximately twenty-four (F = 0.110 ± 0.038 Wm⁻²μm⁻¹sr⁻¹ versus SIF = 2.60 ± 1.87 Wm⁻²μm⁻¹sr⁻¹). In contrast, the average normalized values F_yield and SIF_yield were within the margin of error of one another (F_yield = 0.022 ± 0.008 μm⁻¹sr⁻¹ and SIF_yield = 0.030 ± 0.020 μm⁻¹sr⁻¹). This study highlights the influence of APAR on CF and the importance of properly accounting for it when estimating yield and demonstrates the ability of two simple and portable experimental setups with a passive instrument to obtain fluorescence metrics.

In this study, we attempted to verify the hypothesis that total metals bound to dust of different particle sizes may reflect pollution levels, but cannot predict its bioavailability and risks in human health assessments. Dust samples were collected using active sampling method; during the dry season months of November, 2014 to March, 2015 at different locations in Akure (7˚10ʹN and 5˚15ʹE). The samples were sorted into different particle sizes (< 10µm, 10 – 50 µm, >50µm), analyzed for some physicochemical properties and assessed for metals bioavailability using two-step physiological extraction method. The amount of metals (Cd, Cu, Cr, Ni, Pb, Zn and Mn) released in each particle sizes were determined using Perkin-Elmer 6000 Inductively Coupled Plasma - Atomic Emission Spectrometry (ICP-AES) analysis. The results showed that bioavailability of some metals (Cd, Ni, Pb, and Zn) decreases with increasing particle sizes, however, the reverse trend was observed for Mn, Cu and Fe concentrations. This may be attributed to some combination of physicochemical characteristics of the dust and metal speciation. Hence, it was concluded that metal bioaccessibility in dust can best be described by the knowledge of physicochemical characteristics. The exposure dose of the metals showed that cancer risks due to inhalation were very high when compared to other exposure routes (ingestion and dermal contact). The calculated non-cancer (HQ) and cancer risk (HI) for humans in the area showed values higher than unity, indicating possibility of the metals’ body burden.

A simple approach to enable water-management agencies employing free data to achieve the goal of using a single set of predictive equations for water-quality retrievals with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) were derived using a hybrid forward-selection method that considers Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. The coefficients of determination of the best-fitting resultant equations varied from 0.62 to 0.79. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, solar altitude, and time difference (in days) between the image acquisition and water sampling were found important in water-quality parameter estimation.

Today, non-expensive remote sensing (RS) data from different sensors and platforms can be obtained at short intervals and be used for assessing several kinds of forest characteristics at the level of plots, stands and landscapes. Methods such as composite estimation and data assimilation can be used for combining the different sources of information to obtain up-to-date and precise estimates of the characteristics of interest. In composite estimation a standard procedure is to assign weights to the different individual estimates inversely proportional to their variance. However, in case the estimates are correlated, the correlations must be considered in assigning weights or otherwise a composite estimator may be inefficient and its variance be underestimated. In this study we assessed the correlation of plot level estimates of forest characteristics from different RS datasets, between assessments using the same type of sensor as well as across different sensors. The RS data evaluated were SPOT-5 multispectral data, 3D airborne laser scanning data, and TanDEM-X interferometric radar data. Studies were made for plot level mean diameter, mean height, and growing stock volume. All data were acquired from a test site dominated by coniferous forest in southern Sweden. We found that the correlation between plot level estimates based on the same type of RS data were positive and strong, whereas the correlations between estimates using different sources of RS data were not as strong, and weaker for mean height than for mean diameter and volume. The implications of such correlations in composite estimation are demonstrated and it is discussed how correlations may affect results from data assimilation procedures.

This paper presents a comparison between rain gauges, C-band and X-band radar data over an instrumented and regulated catchment of the Paris region, as well as their respective hydrological impacts with the help of flow observations and a semi-distributed hydrological model. Both radars confirm the high spatial variability of the rainfall down to their space resolution (respectively one kilometer and 250 m) and therefore underscore limitations of semi-distributed simulations. The use of the polarimetric capacity of the Météo-France C-band radar was limited to corrections of the horizontal reflectivity and its rainfall estimates are adjusted with the help of a rain gauge network. On the contrary, neither calibration was performed for the polarimetric X-band radar of the Ecole des Ponts ParisTech (below called ENPC X-band radar), nor any optimization of its scans. In spite of that and the non-negligible fact that the catchment was much closer to the C-band radar than to the X-band radar (20 km vs. 40 km), the latter seems to perform at least as well as the former, but with a higher scale resolution. This characteristic was best highlighted with the help of a multifractal analysis of the respective radar data, which also shows that the X-band radar was able to pick up a few extremes that were smoothed out by the C-band radar.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.

In this research, univariate and bivariate statistical methods were applied to rainfall, river and piezometric level datasets belonging to 24 years long time series (1986-2009). These methods, that often are used to understand the effects of precipitation on rivers and karstic springs discharge, have been used to assess, piezometric level response to rainfall and river level fluctuations in a porous aquifer. A rain gauge, a river level gauge and three wells, located in Central Italy along the lower Pescara river valley in correspondence of its important alluvial aquifer, provided the data. The statistical analysis has been used within a known hydrogeological framework, which has been refined by mean of a photo-interpretation and a GPS survey. Water-groundwater relationships were identified following the autocorrelation and cross-correlation analyses; the spectral analysis and mono-fractal features of time series were assessed, in order to provide information on multy-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical-mathematical results were interpreted through field work that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.

This study assessed the impact of climate change on water availability and variability in two subbasins in the Upper Blue Nile Basin of Ethiopia. Downscaled future climate data from HadCM3 of A2 (medium-high) and B2 (medium-low) emission scenarios were compared to the observed climate data for a baseline period (1961 to 1990). The emission scenario representing the baseline period was used to predict future climate and as input to a hydrologic model to estimate the impact of future climate on the streamflow at three future time horizons 2020 - 2045, 2045 - 2070 and 2070 - 2100. Results suggest that medium-high emission scenario best represents the local rainfall and temperature pattern. With A2 scenario, daily maximum/minimum temperature will increase throughout the future time horizons. The minimum and maximum temperature will increase by 3.6^oC and 2.4^oC, respectively, towards the end of the 21st century. Consequently, potential evapotranspiration is expected to increase by 7.8%, though trends in annual rainfall do not show statistically meaningful trends between years. A notable seasonality was found in the rainfall pattern such that dry season rainfall amounts are likely to increase and wet season rainfall to decrease. The hydrological model indicated that the local hydrology of the study watersheds will be significantly influenced by climate change. Overall, at the end of the century, streamflow will increase in both rivers by up to 64% in dry seasons and decrease by 19% in wet seasons.

Terrestrial LiDAR becomes more and more popular to estimate leaf and plant area density. Voxel-based approaches account for this vegetation heterogeneity and significant work has been done in this recent research field, but no general theoretical analysis is available. Although estimators have been proposed and several causes of biases have been identified, their consistency and efficiency have not been evaluated. Also, confidence intervals are almost never provided. In the present paper, we solve the transmittance equation and use the Maximum Likelihood Estimation (MLE), to derive unbiased estimators and confidence intervals for the attenuation coefficient, which is proportional to leaf area density. The new estimators and confidence intervals are defined at voxel scale, and account for the number of beams crossing the voxel, the inequality of path lengths in voxel, the size of vegetation elements, as well as for the variability of element positions between vegetation samples. They are completed by numerous numerical simulations for the evaluation of estimator consistency and efficiency, as well as the assessment of the coverage probabilities of confidence intervals. • Although commonly used when the beam number is low, the usual estimators are strongly biased and the 95% confidence intervals can be ≈±100% of the estimate. • Our unbiased estimators are consistent in a wider range of validity than the usual ones, especially for the unbiased MLE, which is consistent when the beam number is as low as 5. The unbiased MLE is efficient, meaning it reaches the lowest residual errors that can be expected (for an unbiased estimator). Also the unbiased MLE does not require any bias correction when path lengths are unequal. • When elements are small (or voxel is large), 103 beams entering the voxel leads to some confidence intervals ≈±10%, but when elements are larger (or voxel smaller), it can remain wider than ±50%, even for a large beam number. This is explained by the variability of element positions between vegetation samples. Such a result shows that a significant part of residual error can be explained by random effects. • Confidence intervals are much smaller (±5 to 10%) when LAD estimates are averaged over several small voxels, typically within a horizontal layer or in the crown of individual plants. In this context, our unbiased estimators show a reduction of 50% of the radius of confidence intervals, in comparison to usual estimators. Our study provides some new ready-to-use estimators and confidence intervals for attenuation coefficients, which are consistent and efficient within a fairly large range of parameter values. The consistency is achieved for a low beam number, which is promising for application to airborne LiDAR data. They entail to raise the level of understanding and confidence on LAD estimation. Among other applications, their usage should help determine the most suitable voxel size, for given vegetation types and scanning density, whereas existing guidelines are highly variable among studies, probably because of differences in vegetation, scanning design and estimators.

Assessment of the trends of land cover and vegetation dynamics (VD) using remote sensing (RS) and indicators such as anthropogenic activities and the socio-demographic information is essential in order to make proper planning for sustainable management. This paper attempts to evaluate land cover change (LCC) and VD in Kebbi State, Nigeria using historical Landsat data from 1986-2016 by means of remote sensing. The Driver-Pressure-State-Impact-Response (DPSIR) framework was later employed using both primary and secondary data for a better understanding of the drivers, the state of the environmental condition, the causes as well as the impact of the change. The images were classified into five thematic land cover classes as Dense Vegetation, shrubs/built area, farmland, bare/grassland and water body by means of Maximum likelihood supervised classification technique in accordance with Anderson classification scheme level 1, with acceptable accuracy. Pre-classification and post-classification change detection (CD) methodologies were executed using Normalized difference vegetation index (NDVI) and Image differencing respectively. The study illustrates a steady decline in dense vegetation and shrubs/build areas while farmland and bare/grassland increases, however, water bodies remain unchanged. The DPSIR pin-point that the major drivers of change in the study area have been the pressing need for farming land as the population grows and socioeconomic demands including fuelwood consumption and endemic poverty. Expansion of Farming land, fuelwood consumption and the need for construction materials are identified as the main key elements exerting pressure for the change. The state of the condition indicates a steady decline in dense vegetation and shrubs areas while farmland and bare/grassland are increasing significantly. The impacts include land degradation, the decline in the provision ecosystem goods and services, biodiversity loss through loss of habitats. The study, however, noted that many international and national policies in response to land degradation are channelled toward land restoration and remediating of the environment, through afforestation programs and improving the livelihood of the rural people through providing alternative income sources since they depend heavily on land for sustenance. However, the state governments, communities and individual commonly organized annual tree planting campaign with the main purpose of environmental protection.

Microbial contamination is now more common than chemical contamination in Tibet, and water-borne microbes can cause a number of diseases that threaten public health. Thus, in order to clarify the spatiotemporal distribution of bacteria in small watersheds for which there is no data in Tibet, we set up four sampling points along an upstream-downstream transect of the Xincang River Basin. We collected 239 water samples in 2014 and 2015, and evaluated their total constituent numbers of bacteria (TB) and coliforms (TC). The results of this study show that the microbial contamination of the Xincang River Basin is mild-to-moderate in terms of TB and TC contents, and that these concentrations vary significantly in different seasons. Results show that in summer TB and TC concentrations in the downstream section of this river were highest and that microbial contamination was most serious. Data also demonstrate that precipitation is the most important factor underlying increases in TB and TC concentrations during the summer months; both these variables are significantly correlated with precipitation, while animal husbandry and domestic sewage are the main sources of microbial contamination overall. The results of this study are likely to reflect the basic characteristics of small watersheds for which there is no data to some extent, and are thus of significant practical importance for protecting their ecological environments and promoting sustainable development.

Nicaragua is preparing the construction of an interoceanic canal that will be the longest and largest canal on earth. An environmental and social impact assessment has been published in 2014 supporting a general viability of the canal. Nonetheless, several scientist and societal actors raised serious concerns regarding the social, economic and ecological sustainability. Despite an open dispute within the Nicaraguan society, no independent, transparent and scientifically sound assessment has been carried out. Only the environmental and social impact assessment, charged by the canal constructor, has so far been realized. The aim of this study is to contribute to an open scientific debate through an objective and independent quantification of land use and hydrological impacts. This article presents a transparently documented and comprehensible impact assessment investigation of the West Canal Segment of the Nicaragua Canal. Based on publically available data and scientifically sound and recognized methods land use, hydrological (water availability) and socio-economic impacts (streets, population) are described, quantified and compared with official declarations in the impact assessment. While some results support official declarations other do not. The number of affected population and the water use of the Brito Lock resulted much higher in this study, for instance. Hence, society and water availability could be affected much higher than estimated in the impact assessment.

Unlike the contiguous windthrows, the diffuse windthrows occurred as a result of wind gusts of lower speed (100-140 km/h) than in the first case (>140 km/h) are much more difficult to detect due to their much lower areas and due to their very large number, of several hundreds in the wooded mountain massifs. The objective of this research is to present a rapid procedure for the detection of the diffuse windthrows based on low cost, Landsat type images, knowing that certain sensors cannot be accessed without significant investments. Our application is based on the study of effects caused by the Xynthia storm in the Vosges Mountains in the North-East of France, on 28 February 2010. Thus, based on two sets of Landsat satellite images, we used the “dark object” approach and the Disturbance Index, as well as a classification of the images before and after the storm, resulting in a change map. Following the detection process, 257 scattered polygons were detected, totalling 229 ha. For validation purposes, high-resolution images and orthophotoplans taken before and after storm were used. The error matrix was calculated, achieving an overall accuracy of 86%, which confirms the quality of our analysis and supports this procedure for detecting diffuse windthrow based on low cost resources.

In winter 2008-2009, Lake Occhito, a strategic multiple-uses reservoir in South Italy, was affected by an extraordinary Planktothrix rubescens bloom. P. rubescens is a filamentous potentially toxic cyanobacterium which has recently colonized many environments in Europe. A number of studies is currently available on the use of remote sensing techniques to monitor different fresh water cyanobacteria species. By contrast no specific applications are available on the remote sensing monitoring of P. rubescens. In this paper we present a specific algorithm, based on Water Leaving Reflectances (WLR) from MERIS data, atmospherically corrected using the Aerosol Optical Thickness (AOT) retrieved by MODIS data, to detect P. rubescens blooms. The high accuracy in AOT data, provided by MOD09 surface reflectance product, at 1km spatial resolution, allowed obtaining a good correlation between the WLR and the P. rubescens chlorophyll-a concentrations measured in the field, through multiple stations fluorometric profiles. A modified Normalized Difference Chlorophyll index (NDCI) algorithm is presented. The performance of the proposed algorithm has been successfully compared with other specific algorithms for turbid productive waters. We demonstrated how important is to verify the spectral behaviour of bio-optical parameters in order to develop an ad hoc algorithm that better performs with respect to standard algorithms.

Global change is affecting vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing offer a unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that NDVI has increased over the studied period, particularly at low and middle elevations and during fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily to temperature or precipitation trends. On the other hand, interannual fluctuation in NDVI is more correlated with temperature and precipitation. RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.

Reservoirs are characterized by accumulation of sediments where micropollutants may concentrate, with potential toxic effects on downstream river ecosystems. However, sediment management such as flushing is needed to maintain storage capacity. Climate change is expected to increase sediment loads, but potential effects on their quality are scarcely known. In this context, sediment contamination by trace elements (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) and organics (PAHs, PCBs, C>12) was analyzed in 20 reservoirs located in Italian Central Alps. A strong As and a moderate Cd, Hg and Pb enrichment was emphasized by Igeo, with potential ecotoxicological risk according to PEC quotients. Siltation, granulometry, total organic carbon (TOC) and altitude resulted as the main drivers governing pollutant concentrations in sediments. According to climate change models, expected increase of rainfall erosivity will enhance soil erosion and consequently the sediment flow to reservoirs, potentially increasing coarse grain fractions and thus potentially diluting pollutants. Conversely, increased weathering may enhance metal fluxes to reservoirs. Increased vegetation cover will potentially result in higher TOC concentrations, which may contrast contaminant bioavailability and thus toxicity. Our results may provide elements for a proper management of contaminated sediments in a climate change scenario aiming at preserving water quality and ecosystem functioning.

The growth of urban population, combined with an increase of extreme events due to climate changes call for a better understanding and representation of urban floods. Rainfall and infiltration are two important factors that affect the watershed response to a given precipitation event. In this paper, we evaluate the influence of the representation of infiltration and spatially variable rainfall on the computer simulation of the floods that affected the city of Hull, UK in June 2007. This work compares a uniform rainfall with one generated using Kriging with External Drift and a constant infiltration equal to the soil hydraulic conductivity with a neglected infiltration. The results of the four simulations are then compared with the flood extents observed by public authorities. It results that the computer model is able the reproduce the general dynamic of the flood and identify the main inundated areas. We found that neglecting the infiltration induce a better representation of this flood event. Furthermore, the use of radar rainfall results in an accuracy similar to the one obtained with a constant rainfall. This study indicates that when the spatial resolution of the rainfall data is low compared to the catchment size and the precipitation distribution is uniform, the spatial variability of the rainfall might not add significant information.

Data relating to the rate at which pesticide active substances dissipate on or within various plant matrices are important for a range of different risk assessments; however, despite the importance of this data, dissipation rates are not included in the most common online data resources. Databases have been collated in the past, but these tend not to be maintained or regularly updated. The purpose of the exercise described herein was to collate a new database in a format compatible with the main online pesticide database resource (the Pesticide Properties Database, PPDB), to validate this database in line with the Pesticide Properties Database protocols and thus ensure that the data is maintained and updated in future. Data was collated using a systematic review approach using several scientific databases. Collated literature was subjected to a quality assessment, and then data was extracted into an MS Excel spreadsheet. The outcome of the study is a database based on data collated from 1390 published articles covering over 400 pesticides and over 200 crops across a wide variety of different matrices (leaves, fruits, seeds etc.) for pesticide residues on the crop surface, as well as residues absorbed within the plant material. This data is now fully incorporated into the PPDB.

Terrestrial vegetation dynamics are closely influenced by a multitude of factors. This study investigated the relationships between vegetation patterns and their main influencing factors. The joint entropy method was employed to evaluate the dependence between normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of Hei River basin. Based on the spatial distribution of mutual information, the whole study area was divided into five sub-regions. In each sub-region, nested statistical models were applied to model the NDVI on the grid and regional scales, respectively. Results showed that the annual average NDVI increased with a rate of 0.005/a in recent 11 years. In the desert regions, the NDVI increased significantly with an increase in precipitation and temperature, and high accuracy of retrieving NDVI model was obtained by coupling precipitation and temperature, especially in sub-region I. In the oasis regions, groundwater was also an important factor driving vegetation growth, and the rise of groundwater level contributed to the growth of vegetation. However, the relationship was weaker in artificial oasis regions (sub-region III and sub-region V) due to the influence of human activities, such as irrigation. The overall correlation coefficient between the observed NDVI and modeled NDVI was observed to be 0.97. Outcomes of this study are suitable for ecosystem monitoring, especially under the realm of climate change. Further studies are necessary and should consider more factors, such as runoff and irrigation.

A scenario-based approach to the impacts of land use and climate change can help in identifying future policy directions. This study models the impacts of different land use and climate change scenarios on the forest ecosystems of South Korea to identify national-scale forest policy options. Climatically suitable forest areas for 1,031 climate vulnerable plant species were identified for current time and for 2050. We calculated change in species richness under four climate projections. We built forest conversion models and created four 2050 forest scenarios: (1) forest loss continues at current rates; (2) similar loss, but with conservation in areas with suitable future climates; (3) a reduction of loss by 50%; and (4) a combination of preservation and overall reduction of loss by 50%. We then crossed the forest conversion models with the climate-driven change in species richness, and categorized current forest areas into four classes to offer forest policy alternatives. By deploying the scenarios which preserve climatically suitable forests, the average species richness where forests converting to other land uses reduced significantly. We suggest conserving forests with suitable climates for biodiversity conservation and the establishment of forest plantations targeted to areas where species richness will decline based on our results.

Regional heat capacity change is calculated from the ratio between the addition or subtraction of heat (ΔQ) with the increase or decrease in temperature (ΔT) region. The purpose of this study is to calculate the regional heat capacity change due to the changes of land cover composition with forest, shrubs, oil palm plantation and bare soil using Landsat-5 TM satellite data on 1994, 2000 and 2010. Total area that used on ​​this study is 12971 ha. In 1994-2000, 4 % of forest area and 2% shrubs were increased, followed by additional of biomass forest 4.01 tons/ha and 2.83 tons/ha for shrubs. The increased of forest area and biomass (tons/ha) caused by forest and shrubs growth processing towards climax that added the canopy volume. So that, the regional heat capacity in 1994 amounted 19384 MJC^o-1 increased to 19929 MJC^o-1 in 2000. Data observation for 2000-2010 showed that forest area decreased by 66% due to forest’s clearing into oil palm plantations (47%), shrubs (8%) and bare soil (11%). But, plant’s biomass continue to increased, i.e 1.48 ton/ha for forest, 2.73 tons/ha for shrubs and 4.63 tons/ha for bare soil. Before 2000, there was no land cover by oil palm plantations, so the increasing rate from this land was the biggest than the three other lands, amounting to 122.29 tons/ha. Decreasing in the percentage of forest area does not cause a decrease in the heat capacity of the region. Intensive maintenance on oil plam plantation such as water management, fertilizer and planting space made it biomass productivity and ability to save the heat is greater than the forest. As the result, in 2010 regional heat capacity increased to 22508 MJC^o-1.

Radar altimetry provides valuable measurements to characterize the state and the evolution of the Antartica and Greenland ice sheet cover. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential capacity of complementing the dedicated radar altimeters incrementing the temporal and spatial resolution of the surface height measurements. In this work we perform an study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission, designed primarily to provide sea state information, like sea surface roughness or wind, but not altimetric products. The data has been analyzed with altimetric methodologies, already proved in aircraft based experiments, to extract signal delay observables to be used to infer the topography of the Greenland cover. The penetration depth of the GNSS signals into ice has also considered. The topographic signal obtained is consistent with those obtained with other passive or active microwave sensors. The main conclusion derived from this work is that GNSS-R also provides valuable measurements of the ice sheet cover and, as taken at a variety of geometries and at least two frequency bands, they prospect different depths into the ice. They have thus potential to complement our understanding of the ice firn and its evolution.

Volcanic ash deposited on paved surfaces during volcanic eruptions often compromises skid resistance, which is a major component of safety. We adopt the British pendulum test method in laboratory conditions to investigate the skid resistance of road asphalt and airfield concrete surfaces covered by volcanic ash sourced from various locations in New Zealand. Controlled variations in ash characteristics include type, depth, wetness, particle size and soluble components. We use Stone Mastic Asphalt (SMA) for most road surface experiments but also test porous asphalt, line-painted road surfaces, and a roller screed concrete mix used for airfields. Due to their importance for skid resistance, SMA surface macrotexture and microtexture are analysed with semi-quantitative image analysis, microscopy and a standardised sand patch volumetric test, which enables determination of the relative effectiveness of different cleaning techniques. We find that SMA surfaces covered by thin deposits (~1 mm) of ash result in skid resistance values slightly lower than those observed on wet uncontaminated surfaces. At these depths, a higher relative soluble content for low-crystalline ash and a coarser particle size results in lower skid resistance. Skid resistance results for relatively thicker deposits (3-5 mm) of non-vesiculated basaltic ash are similar to those for thin deposits. There are similarities between road asphalt and airfield concrete, although there is little difference in skid resistance between bare airfield surfaces and airfield surfaces covered by 1 mm of ash. Based on our findings, we provide recommendations for maintaining road safety and effective cleaning techniques in volcanic ash environments.

The aim of this short communication is to find out the legal set up that complies with the environmental management in the textile sector of Bangladesh. This sector is the one of the biggest contributor to the economy of the nation. This sector contributes 81% to the total export earnings involving an immense number of stakeholders to its production processes. It is also true that this sector is largely responsible for the overall environmental pollution through its effluent discharge. The findings suggest that there are both international and national legal guidelines exist for environmental management in the said sector. In order to improve the environmental standards rehearsing lawful instruments is compulsory for the said industries.

The government of Nepal (GoN) has developed and implemented climate policies, plans and frameworks such as NAPA, National Climate Change Policy, LAPA and currently in the process of developing National Adaptation Plans (NAPs). These policies and plans are in different states of its implementation with diverse opinions and perceptions of the stakeholders. The paper has explored these opinions and experiences of climate experts in Nepal on state of climate policies, inter-linkages, roles and responsibilities of ministries/departments, important factors and subjective indicators for effective implementation of the policies. Altogether 30 experts responded the questionnaire sent via the email, LinkedIn and Skype Interview in the 1^st phase of Delphi research technique. The experiences of these experts range from 2-30 years representing government, non-government sectors, media and independent experts. As per most of the experts interviewed, the policies and plans are progressing in strategic direction with national and local priorities. The LAPA is the pioneer framework to address the local climatic issues, originated in Nepal. However, lack of clarity on roles/responsibilities and coordination among the ministries/departments; clear mechanisms for implementation of these policies; lack of sensitization, decentralization and delegation of finance and technologies; capacity of the stakeholders are the major challenges identified.

Mexico´s inhabitants have approximately 7 million dogs and cats as pets, of which there is no accurate information about their environmental impacts as a result of their feeding and comfort requirements. The objective of this study is to compare the environmental footprint between a dog and a cat in a family environment. For this purpose, a life cycle analysis was performed including, among other factors, its feeding and waste management in one year of life. Different environmental indicators including the carbon footprint were considered. It was found that the equivalent CO2 emission of a dog is twice that estimated for a domestic cat and that the main contribution is due to the food production. The ecological footprint that is generated when satisfying the requirements for pet´s well-being impacts in the environment contributes primarily to the carbon footprint.

Agriculture and farming worldwide are responsible for numerous environmental threats, including degradation of land and water resources depletion. Underlining the dynamic interaction between bio-physical and socio-economic drivers is the key towards a more sustainable land and water management. With regard to a highly developed agricultural area in southern Italy, multi-regression models were developed to interpret the observed inter-annual variability of cropped land. Main drivers related to Common Agricultural Policy support, product market prices, crop yield and irrigation water availability were investigated. The adopted models revealed the different weighs of each driver. The findings reported the role that direct payments played in supporting the extension of irrigated crops, such as processing tomato. Likewise, the models pointed to decoupled payment scheme as the most important driver of change in the crop pattern over the last years.

Coastal inundation is an increasing problem. Sea-level rise will greatly increase the frequency and depth of inundation, forcing vulnerable communities to adapt. Communities will need to decide when and how to adapt. The process of decision-making along adaptive pathways is now being used internationally to plan for adaptation over time by anticipating decision points in the future however it unfolds. This process requires risk and uncertainty considerations to be transparent in the scenarios used in such planning. We outline a framework for uncertainty identification and management within coastal hazard assessments which recognizes different types of decision and identifies the types of uncertainty that must be accounted for, such as statistical, scenario and deep uncertainty types. We show how coastal-inundation hazard can be mapped and presented in a way that clearly separates sources of uncertainty, so that they are transparent within a dynamic adaptive pathways planning process. Traditional coastal inundation maps show inundated area only. We present maps of inundation depth and frequency which clearly show the degree of exposure, where that exposure occurs, and how much sea-level rise can be tolerated. The new uncertainty framework and mapping techniques can better identify decision points and their expected time range, which provides more useful input to the adaptation process than traditional coastal inundation assessments.

Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (R_h) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting Ecosystem Respiration (R_eco) to Gross Primary Productivity (GPP). To do so, we developed a simplification of the Soil Carbon dynamics routine proposed in DNDC [1]. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameters distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

Rainfall is the main driver of hydrological processes in dryland environments and characterising the rainfall variability and processes of runoff generation are critical for understanding ecosystem function of catchments. Using remote sensing and in situ data sets, we assess the spatial and temporal variability of the rainfall, rainfall-runoff response, and effects of antecedent soil moisture and ground cover at different spatial scales on runoff coefficients in the Upper Burdekin catchment, northeast Australia, which is a major contributor of sediment and nutrients to the Great Barrier Reef. The high temporal and spatial variability of rainfall exerts significant controls on runoff generation processes. Rainfall amount and intensity are the primary runoff controls, and runoff coefficients for wet antecedent conditions were higher than for dry conditions. The majority of runoff occurred via surface runoff generation mechanisms, with subsurface runoff likely contributing little runoff due to the intense nature of rainfall events. At annual to seasonal temporal scales and for relatively large catchments, we could not detect a significant effect of ground cover on runoff. We conclude that in the range of moderate to large catchments (193 – 36,260 km²) runoff generation processes are sensitive to both antecedent soil moisture and ground cover. A higher runoff-ground cover correlation in drier months with sparse ground cover highlighted the critical role of cover at the onset of the wet season and how runoff generation is more sensitive to cover in drier months than in wetter months. The monthly water balance analysis indicates that runoff generation in wetter months (January and February) is partially influenced by saturation overland flow, most likely confined to saturated soils in riparian corridors, swales, and areas of shallow soil. By March and continuing through October, the soil ‘bucket’ progressively empties by evapotranspiration, and Hortonian overland flow becomes the dominant, if not exclusive, flow generation process. The results of this study can be used to better understand the rainfall-runoff relationships in dryland environments and subsequent exposure of coral reef ecosystems in Australia and elsewhere to terrestrial runoff.

Strategic researches on green mine construction are of great theoretical and practical significance to the sustainable development of China's mining industry as well as the great-leap-forward development strategies of China. Strategies of green mine construction in China are methods summarized to solve all potential problems from mine production to ecological restoration. At present, strategies of green mine construction in China are not fully evaluated and studied yet. Therefore, on the basis of green mine construction related literatures carried out by researchers in China and abroad, this study took the green mine of Yongcheng City in China as the research object to evaluate the current situation of green mine construction in Yongcheng City and put forward corresponding countermeasures. First of all, driving force-pressure-state-impact-response (DPSIR) model was introduced for the construction of evaluation index system; construction principles and selection methods of indexes and the index system based on driving force, pressure, state, impact and response were constructed. Secondly, principal component analysis (PCA) was adopted to calculate and evaluate data of green mine of Yongcheng City in recent years, and construction state of green mine in Yongcheng City was analyzed concretely according to the evaluation results. Empirical results showed that, the evaluation system constructed in this study was feasible, which could be applied to evaluate construction of green mine effectively.

Hydro-climatic projections in West Africa are attributed with high uncertainties that are difficult to quantify. This study assesses the influence of the parameter sensitivities and uncertainties of three rainfall runoff models on simulated discharge in current and future times using meteorological data from 8 Global Climate Models. The IHACRES Catchment Moisture Deficit (IHACRES-CMD) model, the GR4J and the Sacramento model were chosen for this study. During model evaluation, 10,000 parameter sets have been generated for each model and used in a sensitivity and uncertainty analysis using the Generalized Likelihood Uncertainty Estimation (GLUE) method. Out of the three models, IHACRES-CMD recorded the highest Nash-Sutcliffe Efficiency (NSE) of 0.92 and 0.86 for the calibration (1997-2003) and the validation (2004-2010) period respectively. The Sacramento model was able to adequately predict low flow patterns on the catchment while the GR4J and IHACRES-CMD over and under estimate low flow respectively. The use of multiple hydrological models to reduce uncertainties caused by model approaches is recommended along with other methods of sustainable river basin managements.

This paper deals with the environmental characterization of a large and densely populated area, with a poor reputation for contamination, considering the contribution of environmental features (air, soil, soil hydraulic and groundwater) and the potential effects on human health. The use of Geographic Information System (GIS) has made possible a georeferenced inventory and, by overlaying environmental information, an operational synthesis of comprehensive environmental conditions. The cumulative effects on environmental features were evaluated, taking into account superposition effects, by means of the spatial multicriteria decision analysis (S-MCDA). The application of the S-MCDA for converging the combination of heterogeneous factors, related to soil, land and water, deeply studied by heterogeneous groups of experts, constitutes the novelty of the paper. The results confirmed an overall higher potential of exposure to contaminants in the environment and higher mortality rates in the study area for some tumours, but hospital admissions for tumours were generally similar to the regional trend. Besides, mortality data may be strictly dependent on the poor socioeconomic conditions, quality of therapy and a lack of welfare in the area relative to the rest of Italy. Finally, as regards the possible relationship between presence of contaminants in the environment and health conditions of the population no definite conclusions can be drawn, although the present study encourages the use of the new proposed methods, that increase the possibilities for studying the combined effect of more environmental factors.

Is the amount of “greenness” within a 250-meter, 500-meter, 1000-meter or a 2000-meter buffer surrounding a person’s home a good predictor of their physical health? The evidence is inconclusive. We reviewed Web of Science articles that used geographic information systems buffer analyses to identify trends between physical health, greenness, and distance within which greenness is measured. Our inclusion criteria were: (1) use of buffers to estimate residential greenness; (2) statistical analyses that calculated significance of the greenness-physical health relationship; and (3) peer-reviewed articles published in English between 2007 and 2017. To capture multiple findings from a single article, we selected our unit of inquiry as the analysis, not the article. Our final sample included 260 analyses in 47 articles. All aspects of the review were in accordance with PRISMA guidelines. Analyses were independently judged as more, less, or least likely to be biased based on the inclusion of objective health measures and income/education controls. We found evidence that larger buffer sizes, up to 2,000m, better predicted physical health than smaller ones. We recommend that future analyses use nested rather than overlapping buffers to evaluate to what extent greenness not immediately around a person’s home (i.e., within 1,000-2,000m) predicts physical health.

Climate change threatens water, sanitation and hygiene (WaSH) facilities and services, as these are intimately linked to the water cycle and are vulnerable to changes in the quantity and quality of available water resources. Floods and droughts, which pollute and reduce water delivery respectively, have now become a perennial issue to deal with in the northern regions of the country, including the Bolgatanga Municipality. This study aimed to assess the degree to which climate change adaptation measures are mainstreamed into the WaSH development planning process in Ghana. Stakeholders from government and non-government agencies were interviewed to gain perspectives on the threat of climate change, the inclusion of climate change in WaSH planning and the barriers preventing mainstreaming. In general, despite awareness and concern about climate change, adaptation measures have been regarded to be far away from the immediate concerns of WaSH development planning. Most of the current measures are reactive and respond to environmental issues rather than to climate change stressors. In essence, stakeholders expressed the view that the adaptive capacity of the Municipality was low and that mainstreaming has not yet occurred. Despite the lack of progress, there are great opportunities for mainstreaming climate change adaptation into planning through increasing awareness and capacity, legislative and institutional changes and the development of participatory systems to provide early warning systems and disaster risk analyses that will inform future planning.

We present an exact expression for the upscaled dynamic dispersion coefficient (D) for one-dimensional transport by Hagen-Poiseuille flow which is the basis for modeling transport in porous media idealized as capillary tubes. The theoretical model is validated by comparing the breakthrough curves (BTCs) from a 1D advection-dispersion model with dynamic D to that from direct numerical solutions utilizing a 2D advection-diffusion model. Both Taylor dispersion theory and our new theory are good predictors of D at lower Peclet Number (Pe) regime, but gradually fail to capture most parts of BTCs as Pe increases. However, our model generally predicts the mixing and spreading of solutes better than Taylor’s theory since it covers all transport regimes from molecular diffusion, through anomalous transport, and to Taylor dispersion. The model accurately predicts D based on the early part of BTCs even at relatively high Pe regime (~62) where the Taylor’s theory fails. Furthermore, the model allows for calculation of the time scale that separates Fickian from non-Fickian transport. Therefore, our model can readily be used to calculate dispersion through short tubes of arbitrary radii such as the pore throats in a pore network model.

A three-dimensional, unstructured grid, hydrodynamic and suspended-sediment transport model (i.e., SELFE-SED) was developed to simulate temporal and spatial variations of suspended sediment and was applied to the subtropical subalpine Tsuei-Feng Lake (TFL) of Taiwan. The model was validated with measured water level and suspended‑sediment concentration in 2009, 2010, and 2011. The overall model simulation results are in quantitative agreement with the observational data. The validated model was then applied to explore the most important parameter that affects the suspended-sediment concentration and to investigate the effect of wind stress on the mean current and suspended‑sediment distribution in this shallow lake. Modeling results of sensitivity analysis reveal that the settling velocity is a crucial parameter and erosion rate is less important in the suspended-sediment transport model. Remarkable lake circulation was found based on the strength of wind speed and wind direction. Strong wind would result in higher mean current in the top layer and suspended-sediment distribution in the top and bottom layers. This study demonstrated that the wind stress played a significant influence on mean circulation and suspended-sediment transport in a shallow lake.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

Pekalongan is one of several cities that lies in the northern coast of Java island which is often flooded due to sea level rise. This condition impacted its urban development characteristic and increase in the future. In this research both Geographical Information System based and Spatial Metric approach are used. The spatial pattern is analyzed by using spatial metric based on the exploration of land use change that occurred. In this research, the spatial pattern is focused on aggregation pattern and diversity in coastal area. The result shows that the land use of coastal area are dominated with swamp, then followed by settlement and fishpond. It is also shown that the greatest land use change occurred on paddy field and swamp areas. Based on the spatial metric calculation, the aggregation level of land use decrease periodically and has a small growth level. It is indicated from its metric value aggregation and diversity from two periods: 2003-2009 and 2009-2016. Overall the land use of Pekalongan experienced large dynamics, especially in its coastal area. The spatial pattern trend in those area tend to be more sprawl as defined by the decrease of aggregation pattern and low level of land use growth pattern.

Epiphytic lichens are well-known indicators of air contamination. The chemical composition of lichens is affected by the concentration of pollutants in the environment. Usually, researchers assess long-term variations in trace elements or other pollutants in the study area or identify the spatial features of air contamination. The aim of this study is to create a database of trace element concentrations in the samples of the epiphytic lichen Hypogymnia physodes growing in the Kaliningrad region. The database can be used as a ‘reference point’ for monitoring studies. Another objective is to identify the spatial patterns of iron, manganese, nickel, cadmium, silver, lead, strontium, rubidium, and calcium in the Kaliningrad region. The samples of wild lichens were collected from pine and birch trees 1.2-1.8 m from the bases of the threes, using a regular grid, in August 2010. One-two-year-old thalli were used in the chemical analysis. The metals Ag, Cd, Cu, Pb, Ni, Fe, Mn, and Zn were determined by AAS (Mn, Fe by flame AAS and the others by ETA-AAS) and the elements Sr, Rb, and Ca by X-ray fluorescence. The concentration of metals in the western coastal area (the Sambian or Kaliningrad Peninsula) is higher than it is in the central and eastern parts of the region. Principal component factor analysis was carried out to detect and characterise different pollution sources and to identify the most polluted areas. The factors of metal emission were described. The authors examined the features of the spatial distribution of trace elements. Prevailing winds are form south-west. Therefore, the highest concentrations of trace elements were found on the Sambian peninsula and on the coasts of the Vistula and Curonian Lagoons. The high concentrations of trace elements in the samples of the lichen H.physodes, which were observed in the coastal part of the region, are associated with human impact and subsequent pollution. The chemical composition of lichens on the Sambian peninsula may have developed under the impact of both local pollution sources – vehicles, thermal energy facilities, and ports – and such factors as transboundary traffic and sea spray.

Cropland area per capita and pressure index on cropland is the important parameters measuring the social vulnerability and sustainability in the perspective of food security in a certain region in China during the historical periods. This study reconstructs the spatial distribution change of cropland area per labor/household and pressure index on cropland during the 17th-20th century by the methods of historical documents, regression analysis, pressure index model and GIS. Then it analyzed the impacting process of climate change and sustainability of cropland use during the different periods. It draws conclusions: (i) the spatial difference of labor/household density was obvious which had the same pattern as cropland distribution during the same periods, which is higher density in three agricultural areas. (ii) Cropland area per capita was relatively higher during the 17th-18th century, which were above 0.4 ha/person in majority counties and distributed homogenously. Till the 19th century and the beginning of 20th century, cropland area per capita in large amount of regions decreased below 0.2 ha/person embodying the increase of social vulnerability and unsustainability at that time. (iii) Pressure index on cropland also showed the similar spatial pattern as cropland area per capita which presented lower threshold than nowadays. During the 17th-18th century there was no pressure on cropland. While, in the 19th century and at the beginning of 20th century, two high value centers of pressure index on cropland appeared in Middle Shandong and the Jiaodong region, pressure on sustainable cropland use increased obviously and a food crisis is probably created. (iv) Higher sustainable extent of cropland use corresponds to cold period, and lower sustainable extent of cropland use corresponds to warm period in Shandong over the past 300 years. The turning point of 1680s from dry to wet attributes to the decrease of sustainable extent of cropland use in Shandong not very distinctively. More and more pressure on sustainability of cropland use finally since the beginning of 20th century would intensify the social conflict and increase the probability of social revolts.

GNSS have been widely used in navigation, positioning and timing. Nowadays, the multipath errors previously considered detrimental may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), e.g. GPS- Multipath Reflectometry (GPS-MR). In this paper, a new element describing bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model linking the GPS observables (SNR, phase and pseudorange) with detailed vegetation parameters, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that wheat will decrease the amplitudes of GPS multipath observables, if we increase the vegetation moisture contents or the scatters sizes (stem or leaf), the amplitudes of GPS multipath observables (SNR, phase and code) decrease. Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with published results for environmental parameter detections with GPS-MR.

Wetlands are among the most bio-diverse and highest productivity ecosystems on earth, making their monitoring a high priority to conservation, protection and management interests. Although visual interpretation of satellite images is generally precise for monitoring wetlands, recent works have emphasized computerized classification methods because of the reduction in analyst time. However, it is difficult to automatically identify wetland solely based on spectral characteristics due to the complexity of wetland ecosystems. The ability to extract wetland information rapidly and accurately is the basis and the key to wetland mapping at a large scale. Here we propose an operational method to map China wetlands based on Landsat TM data and ancillary data. On the basis of theoretical analysis of wetland automatic classification, we developed a revised multi-layer wetland classification scheme and a rule-based classification model. In the latter, supervised classification (SVM and decision tree) and unsupervised classification (ISODATA) methods were tested. Four Landsat TM images, representing various wetland eco-regions in China (i.e. the Sanjiang Plain in the northeast China, the North China Plain, the Zoige Plateau in the southwest China and the Pearl River Estuary in southeast China), were automatically classified. The overall classification accuracies were 86.57%, 96.00%, 84.51% and 88.30%, respectively, which we considered to be satisfactory accuracy. Our results indicate that issues such as the resolution of geographic data and the understanding of wetland samples should be carefully addressed in the future.

The scarcity and pollution of freshwater are extremely crucial issues today and the expansion of water reuse have been considered as an option to reduce its impact. This study aims to assess the efficiency of an integrated greywater treatment system and hydroponic lettuce production as a part of a green wall structure and to evaluate the health risk associated with the production and consumption of lettuce through quantitative microbial risk assessment (QMRA) and chemical health risk assessment. The study was conducted based on the unique configuration of source separation system; on-site greywater treatment system; green wall structure as a polishing step; and hydroponic lettuce production in the green wall structure. The final effluent from the system was used to grow three lettuce varieties by adding urine as a nutrient solution. Both water samples and plant biomass were collected and tested for E. coli and heavy metals contamination. The system has gained a cumulative 5.1 log10 reduction of E. coli in the final effluent and no E. coli found in the plant biomass. QMRA results indicated that the system attained the health-based targets, 10–6 DALYs per person per year. Similarly, health risk index (HRI) and targeted hazard quotient (THQ) results did not exceed the permissible level, thus the chemical health risk concern was insignificant.

This study investigated the effects of soil crust development on the underlying soil properties. The field sampling work was conducted in June 2016 in the Hobq Desert in Inner Mongolia, North China. Soil crust samples and 0–6, 6–12, 12–18, 18–24, 24–30 cm deep underlying soil samples were taken from five representative areas of different soil crust development stages. All samples were analyzed for physicochemical properties including water content, bulk density, aggregate content, organic matter content, enzyme activities, and microbial biomass carbon and nitrogen. The results showed that the thickness, water content, macroaggregate (>250 μm) content, organic matter content, microbial biomass and enzyme activities of the soil crusts gradually increased along the soil crust development gradient, while the bulk density of the soil crusts decreased. Meanwhile, the physicochemical and biological properties of the soils below the algal and moss crusts were significantly ameliorated when compared with the physical crust. Moreover, the amelioration effects were significant in the upper horizons (approx. 0–12 cm deep) and diminished quickly in the deeper soil layers.

As the largest energy consumer and carbon emitter, China has made substantial efforts to improve energy efficiency for decrease energy consumption, while the energy rebound effect determines its effectiveness. The embodied energy consumption of construction projects accounted for nearly one-sixth of the total economy's energy consumption in China. This paper is based on the logical relationship among capital input, technological progress, economic growth, and energy consumption, adapting an alternative estimation model to estimate the energy rebound effect for the construction industry in China for the first time. Empirical results in our paper reveal that the energy rebound effect for the construction industry in China is about 59.5% for the period of 1990–2014. The results indicate that the energy rebound effect does exist in China’s construction industry and it presented a fluctuating declining trend. This implies that half of the energy savings by technological progress is achieved. In addition, China’s government should implement proper energy pricing reforms and energy taxes to promote the sustainable development of China’s construction industry.

The cruise ship industry has become a well-implemented industry in the Baltic Sea area, and each year, the number of cruise ship passengers rises steadily. Efficient waste management in cruising ports around the Baltic Sea is a crucial element in minimizing environmental impacts. This research involves the four selected ports of Copenhagen, Helsinki, Stockholm and Tallinn. The study applies statistics and interview data to the analysis of waste management systems for cruise ship-generated waste. The interview data involves 14 executives and professionals responsible for environmental issues and decision making in their respective ports. The interviews highlighted the need for standardized environmental legislation and related procedures, which would result in coherent measurement systems. These systems would enable transparent environmental monitoring, thus maintaining the ports’ competitiveness. A common environmental legislation would support the emerging waste management system for the whole Baltic Sea area. We suggest that ports should focus on handling specific types of wastes and collaborate as a spatial network. Specialization to allow discharge of certain fractions of waste is essential. The paper concludes by addressing demands for future research, particularly vessel- and customer behavior focused studies.

The assessment of biomass carbon stocks was conducted at plot scale as a sample to estimate for all vegetation areas by using destructive sampling and or allometric equation method. Remote sensing is one of the techniques can be used to estimate and mapping biomass carbon stock for the entire areas. The objectives of the study are the identification and determine the range of electromagnetic wave of Landsat 8 satellite data that most suitable for assessing and mapping biomass carbon stock distribution. This research analyses exponential regression equation between spectral radiance values (Lλi) for with biomass measurement results on the field to find the best correlation based on the coefficient of determination value (R2). It also analyses the relationship between field biomass and NDVI value (Normal Differences Vegetation Index) from satellite data. The study area consists of 54.9% bush (Bs), 24.5% scrub (Sc), 16.8% secondary forest (Sf), while the rest (3.8%) is a water body. The with average biomass carbon stock value 4.11 tons.ha-1, 64.43 tons.ha-1, and 85.36 tons.ha-1, for strata Sc, Bs, and Sf respectively. Spectral radiance of SWIR (Shortwave Infra-Red) band 6 is determined as a spectral characteristic that can be used to estimating carbon stock with following the equation Y= 12657(EXP(-0.642(Lλband6)) with r2 = 0.75. Correlation NDVI and field biomass showed the low r2 value (0.08), so in this study, NDVI cannot be used to estimate the biomass carbon stock.

This research focuses on the effect of trampling on vegetation in high-mountain ecosystems through the electromagnetic spectrum’s interaction with plant pigments, cell structure, water content and other substances that have a direct impact on leaf properties. The most heavily visited part of the High Tatras in Poland was divided into polygons and, after selecting the dominant species within alpine swards, a detailed analysis of trampled and reference patterns was performed. An ASD FieldSpec 3 was used to acquire high-resolution spectral properties of plants, their fluorescence and the leaf chlorophyll content with the ts-ta temperature index and fraction of accumulated radiation in the range of photosynthesis (fAPAR) used as reference data. The results show that, along tourist trails, vegetation adapts to trampling with the impact depending on the species. A lower chlorophyll value was confirmed by a decrease in fluorescence, and the state of cellular structures was degraded in trampled compared to reference species, with a lower leaf reflectance. Also, at the extreme, trampling can eliminate certain species such as Luzula alpino-pilosa.

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of the Northern Territory of Australia. This work developed and tested a time-series, change-point detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. These cycles were classified to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term (> 3 years) and short term (< 3 years) growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

Water pollution associated with flooding is one of the major problems in cities in the global South. However, studies of water quality dynamics during flood events are not often reported in literature, probably due to difficult conditions for sampling during flood events. Water quality parameters in open water (canals, rivers, and lakes), floodwater on roads and water in sewers have been monitored during the extreme fluvial flood event on 7 October 2013 in Can Tho city, Vietnam. This is the pioneering study of urban flood water pollution in real time in Vietnam. The results showed that water quality is very dynamic during flooding, especially at the beginning of the event. In addition, it was observed that the pathogen and contaminant levels in the floodwater are almost as high as in sewers. The findings show that population exposed to flood water runs a health risk that is nearly equal to that of being in contact with sewer water. Therefore the people of Can Tho not only face physical risk due to flooding, but also exposed to health risk.

Thorium (Th) is a natural radioactive element present in the environment and has a potential to be used as a nuclear fuel. Relatively little is known about the influence and toxicity of Th in the environment. In the present study, the toxicity of Th to the green algae Chlorella pyrenoidosa (C. Pyrenoidosa) was evaluated by algal growth inhibition, biochemical assays and morphologic observations. In the cultural medium (OECD TG 201), Th(NO₃)₄ was transformed to amorphous precipitation of Th(OH)₄ due to hydrolysis. Th was toxic to C. Pyrenoidosa, with a 96 h half maximum effective concentration (EC₅₀) of 10.4 μM. Scanning electron microscopy shows that Th-containing aggregates were attached onto the surface of the algal cells, and transmission electron microscopy indicates the internalization of nano-sized Th precipitates and ultrastructural alterations of the algal cells. The heteroagglomeration between Th(OH)₄ precipitation and alga cells and enhanced oxidative stress might play important roles in the toxicity of Th. To our knowledge, this is the first report of the toxicity of Th to algae with its chemical species in the exposure medium. This finding provides useful information on understanding the fate and toxicity of Th in the aquatic environment.

Woody vegetation in farmland acts as a carbon sink and provides ecosystem services for local people, but no macro-scale assessments of the impact of management and climate on woody cover exists for drylands. Here we make use of very high spatial resolution satellite imagery to derive wall-to-wall woody cover patterns in tropical West African drylands. In arid and semi-arid Sahel, areas of more people are associated with more trees: mean woody cover is greater in farmlands (12%) than in savannas (6%), and likewise it is higher close to villages than further away. In sub-humid savannas of West Africa, woody cover is generally above 20% and decreases with increasing population density, but remains around 15% in farmlands, independent of rainfall. In the region as a whole, rainfall, terrain and soil are the most important (80%) determinants of woody cover, while management factors play a smaller (20%) role. We conclude that agricultural expansion cannot generally be claimed to cause woody cover losses, and that observations in Sahel contradict simplistic ideas of a high negative correlation between population density and woody cover.

The variations of visibility, PM mass concentration and mixing layer height (MLH) at four major urban-industry regions (Shenyang, Anshan, Benxi and Fushun) in multi-cities of central Liaoning over northeast China were evaluated from 2009-2012 to characterize the dynamics effect on air pollution. The annual mean visibilities were about 13.7±7.8km, 13.5±6.5km, 12.8±6.1km and 11.5±6.8km in Shenyang, Anshan, Benxi and Fushun, respectively. The pollution load (PM×MLH) shown a weaker vertical diffusion in Anshan with a higher PM concentration in the near-surface. High concentrations of fine mode particles may be partially attributed to the biomass burning emissions from September in Liaoning Province and surrounding regions in Northeast China as well as the coal burning during the heating period with lower MLH in winter. The increasing wind speed has a similar change as the increasing of mixing layer height to make the effect on the aerosol vertical diffusion. The visibility on the non haze-fog days was about 2.5-3.0 times higher than that on hazy and fog days. The fine particle concentrations of PM2.5 and PM1.0 on the haze and fog days were ~1.8-1.9 times and ~1.5 times higher than that on no hazy-fog days. The MLH during fog pollution showed more declining trend than haze pollution compared with non haze-fog days. The results of this study could provide the useful information to better recognize the effects of vertical pollutants diffusion on air quality in the multi-cities of central Liaoning over Northeast China.

Sulfate, the main dissolved contaminant in acid mine drainage (AMD), is ubiquitous in watersheds affected by coal and metal mining operations worldwide. Engineered passive bioremediation systems (PBS) are low-cost technologies that remediate sulfate contamination by promoting (1) precipitation of sulfate-bearing compounds, such as schwertmannite and gypsum; and (2) microbially-mediated sulfate reduction (BSR) to sulfide with subsequent precipitation of sulfide minerals. In this study, chemical and sulfur isotopic data are used to infer multiple pathways for sulfate sequestration in the Tab-Simco PBS. By simultaneously monitoring sulfate concentrations and δ34SSO4 values at four sampling points across the PBS, we (1) identified that the organic layer within the bioreactor was the primary site of BSR processes contributing to sulfate sequestration; (2) observed seasonal variations of BSR processes; (3) estimated that initially the BSR processes contributed up to 30% to sulfate sequestration in the Tab-Simco bioreactor; and (4) determined that BSR contribution to sulfate sequestration continuously declined over the PBS operational lifetime. Together, our results highlight the utility of combining geochemical and microbial fingerprinting techniques to decipher complementary processes involved in sulfur cycling in a PBS as well as the value of adding the sulfur isotope approach as an essential tool to help understand, predict, prevent and mitigate sulfate contamination in AMD-impacted systems.

The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

A case-crossover study examined how PM_2.5 from Asian Dust Storms (ADS) affects the number of emergency room (ER) admissions for cardiovascular diseases (CVDs) and respiratory diseases (RDs). Our data indicated that PM_2.5 concentration from ADS was highly correlated with ER visits for CVDs and RDs. The odds ratios (OR) increased by 2.92 (95% CI: 1.22-5.08) and 1.86 (95% CI: 1.30-2.91) per increase 10 µg/m³ in PM_2.5 levels, for CVDs and RDs, respectively. A 10 µg/m³ increase in PM_2.5 from ADSs was significantly associated with increase in ER visits for CVDs among those 65 years of age and older (an increase of 2.77 in OR) and for females (an increase of 3.09 in OR). In contrast, PM_2.5 levels had a significant impact on RD ER visits among those under 65 years of age (OR=1.77). The risk of ER visits for CVDs increased on the day when the ADS occurred in Taiwan and the day after (lag 0 and lag 1); the corresponding risk increase for RDs only increased on the fifth day after the ADS (lag 5). In Taiwan’s late winter and spring, the severity of ER visits for CVDs and RDs increases. Environmental protection agencies should employ an early warning system for ADS to reduce high-risk groups’ exposure to PM_2.5.

A field experiment was conducted for 2 years in Green Tea Laboratory of Saitama Prefectural Agriculture and Forestry Research Center, Iruma, Saitama, Japan from March 2014 to December 2015. Controlled release fertilizers (CRF) or organic fertilizers (ORG) which is the mixture of chicken manure and oil cakewere applied with the amount of 450 kg N ha^-1 yr^-1 in 2014 and 397 kg N ha^-1 yr^-1 in 2015. Nitrous oxide (N₂O) emissionsfrom soil in green tea fields were measured by closed chamber method. The results showed that CRF has significantly lower N₂O compared to ORG. The cumulative N₂O emissions from CRF accounted for 51% of N₂O emissions from ORG fields and 138% of control with no fertilizer treatment. The N₂O flux from the row was higher than that of under the canopy, since fertilizer were applied on the row. However the total emission from the area between the rows was lower than that under the canopy because of the area ratio of row and canopy was 1:5.

Outdoor lighting is becoming increasingly widespread, and residents are suffering from serious light pollution as a result. Residents’ awareness of their rights to protection has gradually increased. However, due to the sometimes-inaccessible nature of residential vertical light incidence intensity data and the high cost of obtaining specific measurements, there is no appropriate hierarchic compensation for residents suffering from different degrees of light pollution. It is therefore important to measure light pollution levels and their damage at the neighborhood scale to provide residents with basic materials for proper protection and to create more politically suitable solutions. This article presents a light pollution assessment method that is easy to perform, is low-cost, and has a short data-processing cycle. This method can be used to monitor residential zone light pollution in other cities. We chose three open areas to test the spatial variation pattern of light intensity. The results are in accordance with spatial interpolation patterns and can be fit, with high precision, using the IDW method. This approach can also be used in 3 dimensions to quantitatively evaluate the distribution of light intensity distribution. We use a mixed-use zone in Beijing known as The Place as our case study area. The vertical illumination at the windows of residential buildings ranges from 2 lux to 23 lux; the illumination in some areas is far higher than the value recommended by CIE. Such severe light pollution can seriously interfere with people's daily lives and has a serious influence on their rest and health. The results of this survey will serve as an important database to assess whether the planning of night-time lighting is scientific and whether it provides residents with a basis for the protection of their rights.

Mercury has a strong environmental impact since both its organic and inorganic forms are toxic and it represents a pollutant of global concern. Liquid Hg is highly volatile and it can be released during natural and anthropogenic processes in the hydrosphere, biosphere and atmosphere. In this study the distribution of Gaseous Elemental Mercury (GEM) and the total and leached mercury concentrations on paints, plasters, roof tiles, concretes, metals, dust and wood structures were determined in the main buildings and structures of the former Hg-mining area of Abbadia San Salvatore (Siena, Central Italy). The mining complex (divided into 7 units) covers a surface of about 65 ha and contains mining structures and managers and workers buildings. In this work, nine surveys of GEM measurements were carried out from July 2011 to August 2015 for the buildings and structures located in the units 2, 3 and 6. Moreover, detailed measurements were performed in February, April, July, September and December 2016 in the edifices and mining structures of Unit 6. GEM concentrations showed a strong variability in terms of space and time mostly depending on the distance from the building hosting driers, furnaces and condensers and ambient temperature, respectively. In the Unit 2 surveys carried out in the hotter period (from June to September) showed GEM concentrations up to 27,500 ng m⁻³, while in the Unit 6 they were on average much higher and occasionally they saturated the GEM measurement device (>50,000 ng m⁻³). Concentrations of total (in mg kg⁻¹) and leached (in μg L⁻¹) mercury measured in different building materials (up to 46,580 mg kg⁻¹ and 4,470 mg L⁻¹ for total and leached mercury, respectively) showed for the same type of material highly variable values in dependence on the edifice or mining structure from which they were collected. The results obtained in this study are of relevant interest for the operational cleanings to be carried out during the reclamation activities.

Air pollution has created a lot of problems in the developed and developing countries. To avoid or reduce these problems, constant monitoring of the air should be ensured. The conventional techniques is costly because it requires a lot of money and time consuming. Biomonitoring has been the alternative method. Moss, lichens and plants are biomonitors available to entrap air pollutants. The aim of this paper is to discuss one of the ways of monitoring air pollution – Moss bag technique. To do this, types, choice, preparation, handling of bags after preparation of moss were discussed. From the literatures consulted, it was discovered that there were differences in the techniques used by the researchers. In all, the use of mosses with emphasis on the employment of moss bag have proved to be a powerful tool in airborne particulate and toxic elements. To conclude, developing countries should focus more on this technique because it will reduce cost of air monitoring.

No doubt pollution is a global problem which must be holistically tackled. In doing this, adequate knowledge of the sources of pollution is important, therefore the aim of this paper is to review source apportionment with reference to top-down and bottom-up methods. In this paper, dispersion modeling, emissions inventory, and sampling methods were discussed. Also, analytical methods involved in top-down source apportionment were mentioned. The two techniques are needed to evaluate pollutants and their sources. Based on these two approaches, pollution control strategy would be developed and decisions can be made in deciding the right approach to solve or reduce the pollution problems.

Daily maximum surface air temperature (Tamax) is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST), a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer) LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland) and two seasons (i.e., growing season and non-growing season). Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub), suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnajökull and Langjökull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangajökull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

Analysis of 49 strains of F. langsethiae originating from northern Europe (Russia, Finland, Sweden, UK, Norway, and Latvia) revealed the presence of spontaneous auxotrophic mutants that reflect natural intraspecific diversity. Our investigations detected that 49.0% of F. langsethiae strains were auxotrophic mutants for biotin, and 8.2% of the strains required thiamine as a growth factor. They failed to grow on vitamin-free media. For both prototrophic and auxotrophic strains, no growth defect was observed in rich organic media. Without essential vitamins, a significant reduction in the growth of the auxotrophic strains results in a decrease of the formation of T-2 toxin and diacetoxyscirpenol. In addition, all analysed F. langsethiae strains were distinguished into two subgroups based on PCR product sizes. According to our results, 26 and 23 strains of F. langsethiae belong to subgroups I and II respectively. We determined that the deletion in the IGS region of the rDNA of F. langsethiae belonging to subgroup II is linked with temperature sensitivity and causes a decrease in strain growth at 30 °C. Four thiamine auxotrophic strains were found in subgroup I, while 21 biotin auxotrophic strains were detected in subgroups II. To the best of our knowledge, the spontaneous mutations in F. langsethiae observed in the present work have not been previously reported.

This study was conducted to explore the potential of superabsorbent polymers (SAPs) from used disposable diapers as soil moisture conditioner. Swelling behavior of the proposed hydrogel in response to external stimuli such as salt solutions, temperature and pH was studied. In addition, laboratory experiments were carried out to evaluate the effects of incorporation hydrogel on germination of bean (Phaseolus vulgaris L.) and pumpkin (C. pepo) seeds. The structure of the superabsorbent was characterized by Fourier transform infrared spectroscopy (FTIR). The results indicate that the proposed SAP exhibited a maximum swelling capacity of 189 g.g-1 of dry gel. It was observed that the swelling capacity decreased with an increase in the ionic strength of the swelling medium. When this SAP was mixed with sandy soil, the mixture was able to lose water more slowly. The seeds germination and seedling growth was remarkably influenced by the application of 0.5, 1.0 and 2.0 w/w% of SAP compared to the untreated soil. Therefore, it follows that it is possible to take advantage of SAPs property from used disposable diapers to retain the moisture in soil as an alternative to value the use of such waste, showing that it has potential for diverse applications in agriculture.

From June 18 to 19, 2013, the Ésera river in the Pyrenees, Northern Spain, caused widespread damage due to flooding as a result of torrential rains and sustained snowmelt. We estimate the contribution of snow melt to total discharge applying a snow energy balance to the catchment. Precipitation is derived from sparse local measurements and the WRF-ARW model over three nested domains, down to a grid cell size of 2 km. Temperature profiles, precipitation and precipitation gradient are well simulated, although with a possible displacement regarding the observations. Snowpack melting was correctly reproduced and verified in three instrumented sites, and according to satellite images. We found that the hydrological simulations agree well with measured discharge. Snowmelt represented 33% of total runoff during the main flood event and 23% at peak flow. The snow energy balance model indicates that most of the energy for snow melt during the day of maximum precipitation came from turbulent fluxes. This approach forecast correctly peak flow and discharge during normal conditions at least 24h in advance and could give an early warning of the extreme event 2.5 days before.

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

According to the IPCC guidelines, CO₂ emissions from biomass should be excluded from the entire amount of CO₂ emissions when calculating CO₂ emissions and should be separately reported due to the “carbon neutrality.” Sewage sludge is one of the representative biomass fuels. And it is mixed with fossil fuels in terms of greenhouse gas reduction or is used as fuel to replace fossil fuels by itself. According to the results of this study, biomass contents of both the sewage sludge and the sewage sludge incineration exhaust gases did not amount to 100%. At present, in many countries(South Korea, Japan, and Germany), when calculating greenhouse gas emissions from sewage sludge incinerator, all CO₂ emissions from sewage sludge are judged to be biomass and only those greenhouse gas emissions that correspond to Non-CO₂ gases are calculated as greenhouse gas emissions. However, since, according our results, the content of sewage sludge is not 100% biomass, if CO₂ emissions are excluded according to the existing greenhouse gas emission calculation method, the amount of emissions may be underestimated. Therefore, to accurately calculate greenhouse gas emissions from sewage sludge incinerator, CO₂ emissions should be calculated in consideration of the fossil carbon contents of sewage sludge.

In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better

The Tibetan Plateau(TP) is known as ‘the water tower of Asian’, its precipitation variation play an important role in the eco-hydrological processes and water resources regimes. based on the monthly mean precipitation data of 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2015,variations, trends and temporal-spatial distribution were analyzed, furthermore, the possible reasons were also discussed preliminarily. The main results are summarized as follows: the annual mean precipitation in the TP is 465.54mm during 1961-2015, among four seasons, the precipitation in summer accounts for 60.1% of the annual precipitation, the precipitation in summer half year (May.- Oct.) accounts for 91.0% while that in winter half year (Nov.- Apr.) only accounts for 9.0%; During 1961-2015, the annual precipitation variability is 0.45mm/a and the seasonal precipitation variability is 0.31mm/a, 0.13mm/a, -0.04mm/a and 0.04mm/a in spring, summer, autumn and winter respectively on the TP; The spatial distribution of precipitation can be summarized as decreasing from southeast to northwest in the TP, the trend of precipitation is decreasing with the increase of altitude, but the correlation is not significant. The rising of air temperature and land cover changes may cause the precipitation by changing the hydrologic cycle and energy budget, furthermore, different pattern of atmospheric circulation can also influence on precipitation variability in different regions.

Soil and Water Assessment Tool (SWAT) was used to simulate five glacierized river basins that are global in coverage and vary in climate. The river basins included the Narayani (Nepal), Vakhsh (Central Asia), Rhone (Switzerland), Mendoza (Central Andes, Argentina), and Central Dry Andes (Chile) with a total area of 85,000 km2. A modified SWAT snow algorithm was applied in order to consider spatial variation of associated snow melt /accumulation by elevation band across each subbasin. In the previous studies, melt rates varied as a function of elevation resulting from an air temperature gradient while the snow parameters were constant throughout the entire basin. A major improvement of the new snow algorithm is separating the glaciers from seasonal snow based on their characteristics. Two SWAT snow algorithms were evaluated in simulation of monthly runoff from glaciered watershed: 1) the snow parameters are lumped (i.e. constant throughout the entire basin) and 2) the snow parameters are spatially variable based on elevation band-subbasin (i.e. modified snow algorithm). Applying the distributed SWAT snow algorithm improved the model performance in simulation of monthly runoff with snow-glacial regime, so that mean RSR decreased to 0.49 from 0.55 and NSE increased to 0.75 from 0.69. Improvement of model performance was negligible in simulation of monthly runoff from the basins with monsoon runoff regime.

The global usage of veterinary antibiotics is significant. These antibiotics can be released into the aquatic environment and exert toxic effects on non-target organisms. To explore the physiological effects of tetracycline antibiotics on aquatic life, the growth characteristics of and toxin release from the cyanobacterium Microcystis aeruginosa (M. aeruginosa) were studied. Results showed that the toxicity order of the three target antibiotics was TC (tetracycline) > CTC (chlortetracycline hydrochloride) > OTC (oxytetracycline) in terms of inhibition occurrence time and the EC₁₀ and EC₂₅ values. Further, the target antibiotics regulated the production of MC-LR (microcystin-LR) to different degrees. CTC destroyed the M. aeruginosa cells and resulted in a decreased MC-LR release but stimulated the ability to synthesise MC-LR. OTC had a relatively weaker toxicity compared with CTC, while TC was the most toxic among the three antibiotics. Therefore, TC is friendly to the aquatic environment because it simultaneously reduced the intracellular and extracellular MC-LR content. These results aid our understanding of the effects of tetracycline antibiotics on Microcystis aeruginosa, which is important for environmental evaluation and protection. These results are also helpful for guiding the application of veterinary antibiotics in agricultural settings.

Adaptation to climate change is being addressed in many domains. This means that there are multiple perspectives on adaptation; often with differing visions resulting in disconnected responses and outcomes. Combining singular perspectives into coherent, combined perspectives that include multiple needs and visions can help to deepen the understanding of various aspects of adaptation and provide more effective responses. Such combinations of perspectives can help to increase the range and variety of adaptation measures available for implementation or avoid maladaptation compared with adaptations derived from a singular perspective. The objective of this paper is to present and demonstrate a framework for structuring the local adaptation responses using the inputs from multiple perspectives. The adaptation response framing has been done by: (i) contextualizing climate change adaptation needs; (ii) analyzing drivers of change; (iii) characterizing measures of adaptation; and (iv) establishing links between the measures with a particular emphasis on taking account of multiple perspectives. This framework was demonstrated with reference to the management of flood risks in a case study Can Tho, Vietnam. The results from the case study show that multiple perspective framing of adaptation responses enhance the understanding of various aspects of adaptation measures, thereby leading to flexible implementation practices.

The article focuses on mining of non-energy mineral resources with minimum environmental impacts. It issues from research results of a project Competence Centre for Effective and Ecological Mining of Mineral Resources implemented at the Faculty of Mining and Geology at VŠB-Technical University of Ostrava, Czech Geological Survey, a company Watrad ltd., a state enterprise Diamo, a company RPS Ostrava plc and a company Sedlecký kaolin plc. The paper starts with a partial analysis of the existing legal norms related to mining and processing of mineral resources. Next, it analyses mineral resource mining options free of negative environmental impacts. The fundamental tool to assess potential environmental impacts of mining is the implementation of Environmental Impact Assessment (EIA) process for a given mineral resource. In the Czech Republic environmental impact assessment is carried out by course of Act 100/2001 Coll. Its important amendment is Act 39/2015 Coll. claiming, inter alia, that the environmental impact assessment is rigidly connected with other permits and procedures, such as the zoning process and building construction permits. The article describes the environmental impacts of mining of non-energy mineral resources, including the following factors: appropriation of land, impacts on surface water, ground water and soil, noise, influence on the landscape character, and air pollution. The paper also includes a case study summarizing information on the environmental factors that may play a role in potential underground mining of graphite in the deposit Český Krumlov - Městský Vrch and the deposit Lazec - Křenov.

Camelina (Camelina sativa L.) is an oilseed with potential for use as a raw material in second-generation biofuels. Camelina has a seed yield of up to 2380 kg ha^-1 and contains around 45% fatty acids. Selection of a suitable site is critical for production optimization. The objective of this study was to determine Chilean agro-climatic suitability for establishing camelina as a productive alternative. Climate and soil requirements and geographical restraints were evaluated for the species, considering the climatological characteristics of its regions of origin, as well as regions where camelina is successfully grown in the rest of the world. The variables considered include factors (maximum temperatures of the warmest month, water deficits, and degree days) and limitations (altitude, geomorphology, and current land use), which permitted the evaluation of the national territory for a certain level of suitability. It was determined that 1.3% of the national territory (960,664 ha) has some degree of suitability for camelina adoption. Between the Biobío and Los Lagos regions, 49.0% of land (471,203 ha) is in the category of without thermic restrictions, with mild water restrictions, and mild soil restrictions or without information, which can be used for camelina production. The Los Ríos region had 21.4% surface area (321,176 ha) with some level of suitability for camelina, the most suitable region to establish this crop in Chile.

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

Agro-meteorology is the relationship between agriculture and weather. All farm activities are affected by weather. Therefore it is always necessary to monitor the weather as a forecast. The aim of the research was to monitor the weather and rainwater samples obtained at Federal College of Agriculture, Akure, Ondo State, Nigeria. For the eight months periods, results were obtained. The mean results for the physicochemical parameters were: TDS (12.25 mg/L), temp (28.13 ^oC), pH (6.63), EC (24.25µS/cm), Free CO₂ (24.38mg/L), nitrate (0.16mg/L), phosphate (0.17mg/L), sulphate (0.18mg/L). The rainwater was colorless and had no odor. The mean meteorological data: The prevailing wind directions were from SE, mostly in May, June, July and November and NE. The dry and wet temperatures were 22-29 ^oC and 20-26 ^oC respectively. The maximum value was observed in the month of July. The correlation matrix showed that there were many strong correlations in the physicochemical properties. The months of May, June and July had the highest wind speed. In these months there would be a need to use a windbreaker around the crops planted to avoid soil erosion and damaging of plants.

Crop productivity is directly dependent to soil fertility. High soil organic carbon (SOC) content in soil is vital as it leads to improved soil quality, increased productivity, and stable soil-aggregates. In addition, with the signing of the climate agreement, there is growing interest in carbon sequestration in landscapes. This paper looks at how SOC can be increased so that it not only contributes to reduction of CO₂, but also translates to increased food production thereby enhancing food security. This synergy between mitigation and enhancing food security is even more relevant for mountain landscapes of the Hindu Kush Himalayan (HKH) region where there remains huge potential to increase CO₂ sequestration and simultaneously address food security in the chronic food deficit villages. Soil samples were collected from seven transects each in Bajhang and Mustang and from 4 land use types in each transect. Samples of soils were taken from two depths in each plot; 0-15 cm below the soil surface and 15-30 cm below the soil surface to compare the top soil and subsoil dynamics of the soil nutrients. The lab analysis was performed to assess the soil texture, soil color, soil acidity in 'power of hydrogen' (pH), macro-nutrients as soil fertility. Secondary data was used to analyze the level of food deficit in the villages. The result shows that most of the sample soils from Mustang were clay (82.1%) which is 46 samples out of 56. The pH value of soil from Bajhang ranged from 5.29 to 9.09. The pH value of soil ranged from 5.65 to 8.81 in Mustang. SOC contents of sampled soils from Bajhang ranged from 0.20% to 7.69% with mean amount of 2.47% ± 0.17. SOC contents of sampled soils from Mustang ranged from 0.51% to 8.56% with mean amount of 2.60% ± 0.25. By land use type, forest land had the highest carbon (C) content of 53.61 t ha^-1 in Bajhang whereas in Mustang, agricultural land had the highest C content of 52.02 tons ha-1. Based on these data, we can say that there is potential for increasing SOC through improved soil health and crop production and soil. Sustainable soil management should be practiced for higher productivity. Livestock may also provide farmyard manure, which can be used to fertilize cultivated soils, which increases soil productivity. Increasing productivity would aid in increasing the access and availability of food in these mountain villages.

Although the water absorption feature (WAF) at 970 nm is not very well-defined, it may be used alongside other indices to estimate the canopy water content. The individual performance of a number of existing vegetation water content (VWC) indices against the WAF is assessed using linear regression model. We developed a new Combined Vegetation Water Index (CVWI) by merging indices to boost the weak absorption feature. CVWI showed a promise in assessing the vegetation water status derived from the 970 nm absorption wavelength. CVWI was able to differentiate two groups of dataset when regressed against the absorption feature. CVWI could be seen as an easy and robust method for vegetation water content studies using hyperspectral field data.