Comparative analysis of forest canopy mapping methods for the Sundarban biosphere reserve,West Bengal,India

The canopy density of forests is highly influenced by population pressure which cause forest fragmentations, deforestations, forest degradation and also land reclamation for infrastructure and agriculture. This study was envisaged with the objective of mapping the forest canopy density with two different methods by using Landsat 8 OLI dataset of the year 2016 after mapping the vegetation indices. One of the two methods is the semi-expert FCD mapper model, while the other model is newly developed by us and consists of eight vegetation indices. After running the models, the results of both the models were compared. It was found that for the semi-expert FCD model, the three classes viz. high canopy density, moderate canopy and low canopy covered an area of 81,615.51 ha (40%), 84,474.72 ha (41%) and 38,844.18 ha (19%), respectively. And for the modified FCD model, the same classes covered 69,134.670 ha (37%), 84,062.250 ha (45%) and 32,529.150 ha (18%), respectively. It was observed that the difference between semi-expert FCD model and the modified FCD model’s accuracy is about 1.75% and difference in Kappa statistics is 0.0362. Thus, the modified model is more accurate than the semi-expert FCD model and gives us more detailed canopy density map than the semi-expert FCD map.

     

Pollution-Adjusted Productivity Changes: Extending the Färe–Primont Index with an Illustration with French Suckler Cow Farms

Environmental Modeling & Assessment - Several approaches have been proposed in the literature to compute technical efficiency indices that account for bad outputs. The literature is, however,...     

Illegal landfill in Italy (EU)—a multidisciplinary approach

Illegal dumping of solid waste is a matter of recent concern because of its numerous impacts. The regulatory framework of the European Union and Italy is disclosed. Degradation of air, bodies of water, groundwater, and soil can occur in the illegal landfill and surrounding sites causing e.g. acidification, eutrophication global warming and photochemical smog. Animals and plants are subjected to landfill borne pollutants that can damage them seriously. Landfill pollutants have also harmful effects on human beings raising the risk of illness such as cancer and cardiorespiratory disease. Finally illegal landfilling practices lead to economical, aesthetic impacts, and sociological discomfort that lead to multiple collective actions, blockages, and information campaigns, rising sense of belonging.     

Heavy metals detection in river water with cantilever nanobiosensor

Abstract

Heavy metals can be highly toxic depending on the dose and the chemical form. In this context, sensing devices such as nanobiosensors have been presented as a promising tool to monitor contaminants at micro and nanoscale. In this work, cantilever nanobiosensors with phosphatase alkaline were developed and applied to detect heavy metals (Pb, Ni, Cd, Zn, Co, and Al) in river water. The nanobiosensor surface was functionalized by the self-assembled monolayers (SAM) technique using 16-mercaptohexadecanoic acid, N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide (EDC) and N- hydroxysuccinimide (NHS), and phosphatase alkaline enzyme. The sensing layer deposited on the cantilever surface presented a uniform morphology, at nanoscale, with 80?nm of thickness. The nanobiosensor showed a detection limit in the ppb range and high sensitivity, with a stability of fifteen days. The developed cantilever nanobiosensor is a simple tool, suitable for the direct detection of contaminants in river water.     

A Mathematical Framework for Resilience: Dynamics,Uncertainties, Strategies,and Recovery Regimes

Resilience is a rehashed concept in natural hazard management—resilience of cities to earthquakes, to floods, to fire, etc. In a word, a system is said to be resilient if there exists a strategy that can drive the system state back to “normal” after any perturbation. What formal flesh can we put on such a malleable notion? We propose to frame the concept of resilience in the mathematical garbs of control theory under uncertainty. Our setting covers dynamical systems both in discrete or continuous time, deterministic or subject to uncertainties. We will say that a system state is resilient if there exists an adaptive strategy such that the generated state and control paths, contingent on uncertainties, lay within an acceptable domain of random processes, called recovery regimes. We point out how such recovery regimes can be delineated thanks to so-called risk measures, making the connection with resilience indicators. Our definition of resilience extends others, be they “à la Holling” or rooted in viability theory. Indeed, our definition of resilience is a form of controllability for whole random processes (regimes), whereas others require that the state values must belong to an acceptable subset of the state set.     

Easy and fast extraction methods to determine organochlorine pesticides in sewage sludge,soil, and water samples based at low temperature

Organochlorine pesticides present in sewage sludge can contaminate soil and water when they are used as either fertilizer or agricultural soil conditioner. In this study, the technique solid–liquid extraction with low temperature purification was optimized and validated for determination of ten organochlorine pesticides in sewage sludge and soil samples. Liquid–liquid extraction with low temperature purification was also validated for the same compounds in water. Analyses were performed by gas chromatography-mass spectrometry operating in the selective ion monitoring mode. After optimization, the methods showed recoveries between 70% and 115% with relative standard deviation lower than 13% for all target analytes in the three matrices. The linearity was demonstrated in the range of 20 to 70 µg L^?1, 0.5 to 60 µg L^?1, and 3 to 13 µg L^?1, for sludge, soil, and acetonitrile, respectively. The limit of quantification ranged between 2 and 40 µg kg^?1, 1 and 6 µg kg^?1, and 0.5 µg L^?1 for sludge, soil, and water, respectively. The methods were used in the study of pesticide lixiviation carried out in a poly vinyl chlorine column filled with soil, which had its surface layer mixed with sludge. The results showed that pesticides are not leached into soil, part of them is adsorbed by the sewage sludge (4–40%), and most pesticides are lost by volatilization.     

Pesticide dispersion by spraying under tropical conditions

Pesticide air pollution by spraying was evaluated under different temperature, humidity and wind climatic conditions in Brazil. Field experiments were performed with application towards the soil and in guava orchards, where spray dispersion was monitored by adding p-aminobenzoic acid (PABA), a fluorescent substance, as a tracer to the water contained in the spray tanks. Samples were collected with filter membranes (Whatman 180025), and the PABA was extracted from the filters by shaking with water in a Petri dish and measured in a spectrofluorometer. A spray aimed towards the soil with filters positioned on the ground and hung at different heights did not show different upward dispersion as observed when lateral pulverization was conducted. In this case, a tractor with a sprayer moved through a 3 m high and 6 m wide frame with filter membranes mounted at 60 cm intervals. Spray dispersion patterns were modified by guava leaf resistance. No influence of temperature and humidity was observed in this short-lived spraying process. Nevertheless, wind drift can occur during airborne dispersion and is an important pesticide pollution source which requires control. Droplets with PABA powered by assisted spraying upwards returned to the ground by gravity and, therefore, did not constitute a vertical source of atmospheric pollution.     

Hospital admissions in Iran for cardiovascular and respiratory diseases attributed to the Middle Eastern Dust storms

Environmental Science and Pollution Research - The main objective of this study was to assess the possible effects of airborne particulate matter less than 10 μm in diameter (PM10)...     

Untangling the proximate causes and underlying drivers of deforestation and forest degradation in Myanmar

Political transitions often trigger substantial environmental changes. In particular, deforestation can result from the complex interplay among the components of a system—actors, institutions, and existing policies—adapting to new opportunities. A dynamic conceptual map of system components is particularly useful for systems in which multiple actors, each with different worldviews and motivations, may be simultaneously trying to alter different facets of the system, unaware of the impacts on other components. In Myanmar, a global biodiversity hotspot with the largest forest area in mainland Southeast Asia, ongoing political and economic reforms are likely to change the dynamics of deforestation drivers. A fundamental conceptual map of these dynamics is therefore a prerequisite for interventions to reduce deforestation. We used a system‐dynamics approach and causal‐network analysis to determine the proximate causes and underlying drivers of forest loss and degradation in Myanmar from 1995 to 2016 and to articulate the linkages among them. Proximate causes included infrastructure development, timber extraction, and agricultural expansion. These were stimulated primarily by formal agricultural, logging, mining, and hydropower concessions and economic investment and social issues relating to civil war and land tenure. Reform of land laws, the link between natural resource extraction and civil war, and the allocation of agricultural concessions will influence the extent of future forest loss and degradation in Myanmar. The causal‐network analysis identified priority areas for policy interventions, for example, creating a public registry of land‐concession holders to deter corruption in concession allocation. We recommend application of this analytical approach to other countries, particularly those undergoing political transition, to inform policy interventions to reduce forest loss and degradation.     

Patterns of biodiversity and habitat sensitivity in agricultural landscapes

Design of landscape is the process of the arrangement of spatial features with the objective of sustaining ecosystem services, and maintaining ecological functionality to meet societal needs. Along a gradient of cultivation intensity, the functional quality of agricultural landscape was explored and the relationships between landscape metrics and functional quality were analyzed, in order to make effective recommendations for landscape design aimed at sustainable land use schemes. The functional quality of landscape was calculated using the InVest model for 20 farm landscapes (North-Eastern Italy) where biodiversity (plant taxa) and sensitivity to disturbance (hemeroby) were used as model inputs. Results highlighted the importance of specific habitat types such as meadows and woodlands rather than other habitats for improving the biodiversity of agricultural landscapes. A high proportion of these habitats enhanced the functional quality of the landscape when the habitats were organized in large and not isolated patches in heterogeneous landscapes.