Indicators Of Environmental Degradation Research Articles

Deforestation as an indicator of environmental degradation: Analysis of five European countries

This study explores the validity of the Environmental Kuznets Curve (EKC) hypothesis for deforestation in France, Germany, Greece, Portugal and Turkey. The autoregressive distributed lag bounds testing approach was applied on time-series data over the period 1974–2013. Deforestation is considered an indicator of environmental degradation for its relevance as a global environmental concern, being agriculture expansion one of its main causes. Nonetheless, Europe has achieved an expansion of its forest region through policies that have promoted the use of technology in the agricultural sector. The results of long-run coefficients suggest an inverted U-shaped relationship between deforestation and Gross Domestic Product (GDP) per capita in France, Germany, Portugal and Turkey, which supports the EKC hypothesis. Based on the empirical results, we conclude that an increment in agricultural exports does not contribute to an increment in deforestation. Recommendations regarding public policies derive from the analysis of the Granger causality test. For example, deforestation reduction and investment on deforestation reduction will not hurt economic growth in all countries except Greece.

Risk assessment and driving factors for artificial topography on element heterogeneity: Case study at Jiangsu, China.

The rapid expansion of construction related to coastal development evokes great concern about environmental risks. Recent attention has been focused mainly on factors related to the effects of waterlogging, but there is urgent need to address the potential hazard caused by artificial topography: derived changes in the elemental composition of the sediments. To reveal possible mechanisms and to assess the environmental risks of artificial topography on transition of elemental composition in the sediment at adjoining zones, a nest-random effects-combined investigation was carried out around a semi-open seawall. The results implied great changes induced by artificial topography. Not only did artificial topography alter the sediment elemental composition at sites under the effect of artificial topography, but also caused a coupling pattern transition of elements S and Cd. The biogeochemical processes associated with S were also important, as suggested by cluster analysis. The geo-accumulation index shows that artificial topography triggered the accumulation of C, N, S, Cu, Fe, Mn, Zn, Ni, Cr, Pb, As and Cd, and increased the pollution risk of C, N, S, Cu, As and Cd. Enrichment factors reveal that artificial topography is a new type of human-activity-derived Cu contamination. The heavy metal Cu was notably promoted on both the geo-accumulation index and the enrichment factor under the influence of artificial topography. Further analysis showed that the Cu content in the sediment could be fitted using equations for Al and organic carbon, which represented clay mineral sedimentation and organic matter accumulation, respectively. Copper could be a reliable indicator of environmental degradation caused by artificial topography.

Effects of Three Selected Pesticides on the Non-Biting Midges (Diptera: Chironomidae) in Rice Agro-Ecosystem of an area of West Bengal; India

Deformities of non biting midge larvae’s mouthparts are considered as indicators of environmental degradation that caused by water pollutants like pesticides, heavy metals, organic contaminants etc. The present investigation was aimed to assess the effects of 3 pesticides, viz. Cartap Hydrochloride, Carbofuran and Fipronil on deformities of chironomid larvae of the Rice fields of Village Dhunui; Memari Block-II of Burdwan district in West Bengal. The study area is dominated by the species of the genus Chironomus of chironomid community. Concurrently six (6) species were considered. The average percentage of mouthpart deformities was 14% in all chironomid larvae. Highest degree of malformation was noticed in Chironomus circumdatus in which more than 18.90% of all specimens were affected. However, further investigative efforts are essential to investigate the actual explanation in support of the occurrence of high degree of deformities in chironomid.

Biodiversity: The Non-natives Species Versus the Natives Species and Ecosystem Functioning

The loss of biodiversity is one of the most reflective effects of humans on the global perspective and it is more and more urgent to understand how this loss will affect and what will be the profound consequences to the ecosystem functioning. Non-native fishes can cause considerable adverse impacts on the function of aquatic ecosystems and loss of biodiversity. Ecology of ecosystem focuses on the fluctuation of energy and nutrients through ecological systems. It has been confirmed that the fishes are sensitive indicators of environmental degradation and alteration. Study was undertaken during the period of October 2015 to September 2016 from the Paisuni river, India. Fish faunas of the Paisuni river have harbors of 58 species belonging to 5 order, 18 family and 43 genera. Cypriniformes and Cyprinidae were the most rich fish species order and families, respectively from the river. The Cyprinidae family has highest harbors family with 25 fish species. The family Anabaniitidae has 5 fish species which is second dominant family from the Paisuni river. According to abundance, Cyprinus carpio and Oreochromis niloticus were powerfully invaded in the Paisuni river. The detonated frequency of O. niloticus and C. carpio was recorded from the Paisuni river. Exotic species is alarming for indigenous fish species biodiversity. C. carpio and O. niloticus are frequently recorded in the Ganga river. Very highly important and ecological indicator fish species, Tor mahseer, Tor tor is declining in the catch. Current ecosystem functioning is favour to non-native species from the Paisuni river.

The impact of economic development on environmental degradation in Qatar

This study investigates the environmental Kuznets curve (EKC) hypothesis by employing the ecological footprint (EF) as an indicator of environmental degradation in Qatar over the 1980–2011 period. The results of the Autoregressive Distributed Lag (ARDL) estimation with structural breaks reveal that there is a long run relationship among the selected variables with a significant shift in the cointegration vector in 1996. The comparison of the short and long-run income elasticities indicates that the EKC hypothesis is not valid in Qatar. In particular, the long run effect of income is greater than its short run effect, which provides evidence of a monotonic relationship between EF and real GDP per capita. Moreover, the oil price and trade openness have a positive and negative long run impact on ecological footprint, respectively. We further investigate the robustness of the results by employing the Toda–Yamamoto causality tests and the estimation with regime approach. The outcome of TY shows that income and oil price increase significantly the ecological footprint. Moreover, the results of the estimation with two regimes (1980–1996 and 1997–2011) show that the impact of real GDP on the EF in the second regime is higher than the first regime, which confirm the ARDL estimation results.

Poverty and Environmental Degradation in Southern Burkina Faso: An Assessment Based on Participatory Methods

The poverty and environmental degradation vicious circle hypothesis considers the poor as agents and victims of environmentally degrading activities. Despite some studies, however, there still has not been a sufficient empirical examination of the poverty-environment nexus. Based on participatory poverty assessment (PPA) methods with two hundred farm households categorized by wealth status in southern Burkina Faso, six indicators of environmental degradation and a set of land management practices were examined to answer the following questions: (i) Which households (non-poor, fairly-poor, or poorest) are responsible for environmental degradation? (ii) Does poverty constrain adoption of land management practices considered to improve the land? Results indicate deforestation is highest for non-poor farmers, and non-poor and fairly-poor farmers have higher rates of overgrazing. In addition, the entire non-poor group, mainly recent migrants to the area, occupy borrowed lands with tenure perceived as insecure, considered by farmers to be a disincentive for assisted natural regeneration of vegetation. Thus, non-poor and fairly-poor farmers participate most in activities locally identified as environmentally degrading, and the former contribute more than the latter. On the other hand, adoption of land management practices considered to improve the land is relatively low amongst the poorest farmers.

From Objective Environmental Problems to Subjective Environmental Concern: A Multilevel Analysis Using 30 Indicators of Environmental Quality

ABSTRACTThis article analyzes the effect of environmental degradation, the affluence hypothesis, and postmaterialist theory to assess the environmental concern of individuals in 51 countries. The hypotheses are tested using a multilevel analysis that employs an unprecedented number of objective indicators of environmental degradation, using the World Values Survey 6th wave (2010–2014). The results support the degradation hypotheses, where the importance of water scarcity in a country and national biodiversity are the major variables that explain individual environmental concern among all the indicators of environmental degradation. The affluence hypothesis is rejected and the postmaterialist theory is supported only at the individual level.

Providing a Model for Assessing the Quality of the Natural Environment in Rural Areas Using Knowledge-Based Systems

Providing a Model for Assessing the Quality of the Natural Environment in Rural Areas Using Knowledge-Based Systems

Ecological footprint: an indicator of environmental sustainability of a surface coal mine

Ecological footprint of mining can be used as an indicator to monitor and regulate mining operations and ensure long-term environmental sustainability. It can be viewed as a mining footprint, which is surrogate of the environmental impacts of mining. In this paper, a methodological framework is developed to demonstrate how ecological footprint can be used as an indicator of environmental degradation. Nine air quality and 26 soil quality samples are collected from the adjoining area of a mechanized coal mine, located in Raniganj coal mining belt of Burdwan district, West Bengal. Geographical information system is used for data interpolation and preparation of air and soil quality maps. The weights of different air and soil quality parameters are calculated by running principal component analysis. These derived weights are used for preparation of final composite air and soil quality maps. The composite maps show the mining footprints, expressed as land equivalent, around the active mine sites. The impact zones reveal the extent of degradation of the soil and air qualities in the areas near a mine. It is found that the impact zones, with respect to air and soil qualities, extend over areas which are 7.7 and 7.8 times the actual mining areas, that is, the area covered under mining operations, respectively. The results show the extent of degradation of air and soil qualities of the area. At different stages of mining, these footprints can be used as indicators to reveal the areas where soil and air qualities are adversely impacted.

Curva Ambiental de Kuznets: evidencia empírica para la economía peruana, periodo 1972 - 2010

The objective of this research is to determine the existence of the relationship between economic growth and environmental degradation for the Peruvian economy from 1970 to 2010. To test the hypothesis (U-inverted) Environmental Kuznets Curve, the Johansen cointegration technique and Pesaran, Shin and Smith was used. It is found that there is a linear relationship between increasing emissions of carbon dioxide (CO2) and sulfur dioxide (SO2) as indicators of environmental degradation with the GDP per capita, together with trade liberalization, percentage of population urban and consumption of fossil fuel. Therefore, it is concluded that the Peruvian economy, in the study period, there is a positive relationship between economic growth and environmental degradation, that is, is in the first stage of the Environmental Kuznets Curve.

Artificial neural networks as an indicator search engine: The visualization of natural and man-caused taxa variability

One of the main challenges in selecting suitable biological indicators of environmental degradation is to recognize the stressor-specific response signal and to separate it from the natural background variability, which can be accomplished by setting an appropriate statistical design, with an output that enables understanding of the recorded indicator signal. In this study we used artificial neural networks (self organizing map (SOM) and geo-self-organizing map (Geo-SOM)) to model and visualize the variability in the chironomid community of the Danube basin, as a model for large non-wadeable rivers. Geo-SOM analysis visualized the longitudinal distribution of significant parameters defining different spatial-distributional types of anthropogenic disturbance. Chironomidae larvae, sampled in both shallow (river bank) and deep (middle) parts of the river, emphasized hydromorphological degradation and zinc as the most important stressing factors, with chlorophyll-a and suspended solids as accompanying variables influencing the community structure. Substrate specificity was shown to be a relevant factor influencing the variability within chironomid community structure bound to natural causes. Geo-SOM analysis also visualized the longitudinal distribution of chironomid taxa, following the distribution patterns of significant disturbance factors. The Kruskal–Wallis test validated 25 potential indicators for the shore area and 11 for the deep water area, which significantly changed their frequencies and abundances between classes with different extents of degradation. Due to its high taxonomical and ecological diversity, the Chironomidae family is a significant source of potential stress-specific indicators, which should be recognized and included in the future in relevant bioassessment methods. The artificial neural network could be a powerful tool for selecting reliable indicators to explain the variability found in the ecosystem and enable it to be specified and patterned together with environmental degradation.

Production and consumption-based approaches for the environmental Kuznets curve using ecological footprint

ABSTRACTWe examine the environmental Kuznets curve (EKC) hypothesis using the ecological footprint (EF), a more comprehensive indicator of environmental degradation, for 11 countries covering the 1971–2007 period. We test the EKC hypothesis using a traditional quadratic function from both the supply and consumption side, adding several explicative variables: urbanisation, petrol price and industrialisation for the supply side; biocapacity, life expectancy and energy use for the consumption side. We perform an autoregressive distributed lagged modelling in order to study both short- and long-run periods. We find that there is no stable relationship between the environment and economic development in the long-run. For the short-run analysis, the EKC hypothesis is supported for no one, we rather find an increasing relationship between growth and environment. Results for explicative variables are mixed: for the production-side approach, industrialisation appears to have a positive impact on EF for Sweden, but a negative one for Portugal and Spain. For the consumption-side approach, energy use seems to have a positive impact on EF for Argentina and Colombia whereas biocapacity and life expectancy have a positive and negative impact, respectively, on EF for Paraguay. Lastly, biocapacity has a positive impact on EF for Canada but negative for Norway, likely depending on levels of biocapacity and ecological reserve.

Global occurrence of anti-infectives in contaminated surface waters: Impact of income inequality between countries

The presence anti-infectives in environmental waters is of interest because of their potential role in the dissemination of anti-infective resistance in bacteria and other harmful effects on non-target species such as algae and shellfish. Since no information on global trends regarding the contamination caused by these bioactive substances is yet available, we decided to investigate the impact of income inequality between countries on the occurrence of anti-infectives in surface waters. In order to perform such study, we gathered concentration values reported in the peer-reviewed literature between 1998 and 2014 and built a database. To fill the gap of knowledge on occurrence of anti-infectives in African countries, we also collected 61 surface water samples from Ghana, Kenya, Mozambique and South Africa, and measured concentrations of 19 anti-infectives. A mixed one-way analysis of covariance (ANCOVA) model, followed by Turkey–Kramer post hoc tests was used to identify potential differences in anti-infective occurrence between countries grouped by income level (high, upper-middle and lower-middle and low income) according to the classification by the World Bank. Comparison of occurrence of anti-infectives according to income level revealed that concentrations of these substances in contaminated surface waters were significantly higher in low and lower–middle income countries (p=0.0001) but not in upper–middle income countries (p=0.0515) compared to high-income countries. We explained these results as the consequence of the absence of or limited sewage treatment performed in lower income countries. Furthermore, comparison of concentrations of low cost anti-infectives (sulfonamides and trimethoprim) and the more expensive macrolides between income groups suggest that the cost of these substances may have an impact on their environmental occurrence in lower income countries. Since wastewaters are the most important source of contamination of anti-infectives and other contaminants of emerging concern in the environment, it is expected that deleterious effects to the aquatic biota caused by these substances will be more pronounced in countries with inadequate wastewater and collection infrastructure. With the information currently available, we could not evaluate either the role of the receiving environment or the importance of regulatory frameworks on the occurrence of anti-infectives in surface waters. Future studies should focus on these two factors in order to better evaluate risks to aquatic ecosystems in LM&LICs. We propose that CECs such as anti-infectives could be used as a new class of environmental degradation indicators that could be helpful to assess the state of development of wastewater collection and treatment infrastructure around the world.

Decoupling Economic Growth and Environmental Degradation: Reviewing Progress to Date in the Small Island State of Malta

This paper considers the challenge of decoupling economic growth from environmental degradation; in contrast to several large-scale cross-country analyses that focus on limited indicators of environmental degradation, we analyze in some depth the experience of a single small-scale island state setting (Malta). We use available statistical data to derive decoupling factors, in order to consider the extent to which decoupling has been achieved in four sectors: (i) energy intensity, climate change, and air quality; (ii) water; (iii) waste; and (iv) land. Results indicate relative decoupling between economic growth and several indicators considered, and to a lesser extent, relative decoupling between population growth and the same indicators of environmental pressure. Absolute decoupling has been achieved in at least one instance but there has been no decoupling of land development from either economic or population growth. Land use and population thus appear to be notable sources of pressure. The results suggest that decoupling analyses that present environmental degradation in terms of single variables (e.g., carbon emissions) may misrepresent somewhat the state of the environment at local level. Furthermore, the study highlights the need for methodologies that factor in the “embedding” of small-scale settings within much larger trade networks, for a more accurate estimation of environmental impact, and points to some limitations of solely quantitative analyses of environment-ecology relationships.

Environmental correlates of mental health measures for women in Western Australia.

A recent study in Western Australia identified area level associations between soil salinisation and hospital admissions for depression. Our study assessed the quantitative relationship between mental health measures at the individual level and location specific environmental measurements on salinity, as well as two other indicators of environmental degradation and change: land surface temperature and normalised difference vegetation index, a proxy for rainfall. Location-specific environmental measurements were linked to individual mental health scores of women in three age cohorts from the Australian Longitudinal Study on Women's Health using a geographic information system. Bayesian geostatistical linear regression models were developed to assess associations between environmental exposures and mental health scores of women. In contrast to previous studies using area level measures, our study found no associations between individual level measurements of mental health scores for women in south-west Western Australia and salinity, LST or NDVI.

Investigating the environmental Kuznets curve (EKC) hypothesis by utilizing the ecological footprint as an indicator of environmental degradation

This study investigates the environmental Kuznets curve (EKC) hypothesis using a country’s ecological footprint as an indicator of environmental degradation. Ninety-three countries were examined, categorized by income. The fixed effects and the generalized method of moments results clearly showed an inverted U-shaped relationship between the ecological footprint and GDP growth, which represents the EKC hypothesis in upper middle- and high-income countries but not in low- and lower middle-income countries. This relationship only occurs in a stage of economic development in which technologies are available that improve energy efficiency, energy saving and renewable energy, which are not accessible for countries with low income due to their high cost. Moreover, energy consumption, urbanization, and trade openness increase environmental damage through their positive effect on the ecological footprint of most countries across all income groups. However, financial development reduces environmental degradation in lower middle-, upper middle- and high-income countries. This relationship confirms that loans from banks are primarily given to firms that establish investments in projects that are mostly environmentally friendly. From the results of this study, a number of recommendations can be provided for the investigated countries.

Fossil & renewable energy consumption, GHGs (greenhouse gases) and economic growth: Evidence from a panel of EU (European Union) countries

Recently a great number of empirical research studies have been conducted on the relationship between certain indicators of environmental degradation and income. The EKC (Environmental Kuznets Curve) hypothesis has been tested for various types of environmental degradation. The EKC hypothesis states that the relationship between environmental degradation and income per capita takes the form of an inverted U shape. In this paper the EKC hypothesis was investigated with regards to the relationship between carbon emissions, income and energy consumption in 16 EU (European Union) countries. We conducted panel data analysis for the period of 1990–2008 by fixing the multicollinearity problem between the explanatory variables using their centered values. The main contribution of this paper is that the EKC hypothesis has been investigated by separating final energy consumption into renewable and fossil fuel energy consumption. Unfortunately, the inverted U-shape relationship (EKC) does not hold for carbon emissions in the 16 EU countries. The other important finding is that renewable energy consumption contributes around 1/2 less per unit of energy consumed than fossil energy consumption in terms of GHG (greenhouse gas) emissions in EU countries. This implies that a shift in energy consumption mix towards alternative renewable energy technologies might decrease the GHG emissions.

Effects of damming on the biological integrity of fish assemblages in the middle Lancang-Mekong River basin

The Lancang-Mekong River basin contains a diverse assemblage of freshwater fish species; however, their populations are threatened by current and planned dam construction along the river. Fish assemblages are sensitive indicators of environmental degradation and can be used to assess aquatic ecosystem health. This research compared the fish fauna at the Xiaowan hydropower dam located on the middle reaches of the Lancang-Mekong River at three time periods: in 2008 (before impoundment), 2010 (water storage) and 2011 (full operation). A modified fish index of biological integrity (modified F-IBI) was developed and it synthesized information on the taxonomic composition, trophic guilds, and tolerance levels of the fish and habitat diversity to quantitatively assess the condition of fish populations before and after damming. This index also was used to assess the longitudinal diversity of the fish fauna along the river channel and could assess the barrier effect associated with the dam. Jaccard's index of similarity was used as a feasible tool to assess fish diversity loss and biotic homogenization. The analysis clearly showed a homogenization of the fish communities after damming, and the reservoir impoundment region showed much more serious homogenization than the downstream region. The Xiaowan dam had an immediate and profound effect on the fish fauna in this region of the Lancang-Mekong River. A total of eight cascading dams are planned for development in this region, and, unless conservation mitigation efforts are considered, the results could be devastating on the native fish populations of middle reaches of the Lancang-Mekong River basin.

Directional connectivity in hydrology and ecology

Quantifying hydrologic and ecological connectivity has contributed to understanding transport and dispersal processes and assessing ecosystem degradation or restoration potential. However, there has been little synthesis across disciplines. The growing field of ecohydrology and recent recognition that loss of hydrologic connectivity is leading to a global decline in biodiversity underscore the need for a unified connectivity concept. One outstanding need is a way to quantify directional connectivity that is consistent, robust to variations in sampling, and transferable across scales or environmental settings. Understanding connectivity in a particular direction (e.g., streamwise, along or across gradient, between sources and sinks, along cardinal directions) provides critical information for predicting contaminant transport, planning conservation corridor design, and understanding how landscapes or hydroscapes respond to directional forces like wind or water flow. Here we synthesize progress on quantifying connectivity and develop a new strategy for evaluating directional connectivity that benefits from use of graph theory in ecology and percolation theory in hydrology. The directional connectivity index (DCI) is a graph-theory based, multiscale metric that is generalizable to a range of different structural and functional connectivity applications. It exhibits minimal sensitivity to image rotation or resolution within a given range and responds intuitively to progressive, unidirectional change. Further, it is linearly related to the integral connectivity scale length--a metric common in hydrology that correlates well with actual fluxes--but is less computationally challenging and more readily comparable across different landscapes. Connectivity-orientation curves (i.e., directional connectivity computed over a range of headings) provide a quantitative, information-dense representation of environmental structure that can be used for comparison or detection of subtle differences in the physical-biological feedbacks driving pattern formation. Case-study application of the DCI to the Everglades in south Florida revealed that loss of directional hydrologic connectivity occurs more rapidly and is a more sensitive indicator of declining ecosystem function than other metrics (e.g., habitat area) used previously. Here and elsewhere, directional connectivity can provide insight into landscape drivers and processes, act as an early-warning indicator of environmental degradation, and serve as a planning tool or performance measure for conservation and restoration efforts.

The impact of topographical characteristics and land use change on the quality of Umbaniun micro-watershed water resources, Meghalaya

A watershed is a geohydrological unit draining at a common point. Such natural unit has evolved through rain water interaction with land mass, typically comprising arable land, non-arable land and natural drainage lines in rain-fed areas. Sustainable production depends on the health, vitality and purity of a particular environment in which land and water are important constituents. A pilot study was thus undertaken to study the geomorphology, land-use systems and their impact on water resource management on the Meghalaya Umbaniun micro-watershed. In this Micro-watershed (3951.18 ha), water body covers an area of 5.69ha (0.14%). The paper highlights the linkage between geomorphology, land use systems and its impact on quality of water resources on the Umbaniun Micro-Watershed, Meghalaya. Topographical and physical-chemical characteristics, such as pH, conductivity, dissolved oxygen, turbidity and water temperature, were used as environmental degradation indicators.