Understanding interactions between urban development policies and GHG emissions: A case study in Stockholm Region

Human-induced urban growth and sprawl have implications for greenhouse gas (GHG) emissions that may not be included in conventional GHG accounting methods. Improved understanding of this issue requires use of interactive, spatial-explicit social–ecological systems modeling. This paper develops a comprehensive approach to modeling GHG emissions from urban developments, considering Stockholm County, Sweden as a case study. GHG projections to 2040 with a social–ecological system model yield overall greater emissions than simple extrapolations in official climate action planning. The most pronounced difference in emissions (39% higher) from energy use single-residence buildings resulting from urban sprawl. And this difference is not accounted for in the simple extrapolations. Scenario results indicate that a zoning policy, restricting urban development in certain areas, can mitigate 72% of the total emission effects of the model-projected urban sprawl. The study outcomes include a decision support interface for communicating results and policy implications with policymakers.

     

The influence on carbon,nitrogen recycling,and greenhouse gas emissions under different C/N ratios by black soldier fly

Environmental Science and Pollution Research - Currently, sustainable utilization, including recycling and valorization, is becoming increasingly popular in waste management. Black soldier fly...     

Molecular,functional, and cellular alterations of oocytes and cumulus cells induced by heat stress and shock in animals

Environmental Science and Pollution Research - Global warming is considered as the main environmental stress affecting ecosystems as well as physiological and biochemical characteristics, and...     

Hurricane Harvey and Greater Houston households: comparing pre-event preparedness with post-event health effects,event exposures,and recovery

Most disaster studies rely on convenience sampling and ‘after-only’ designs to assess impacts. This paper, focusing on Hurricane Harvey (2017) and leveraging a pre-/post-event sample of Greater Houston households (n=71) in the United States, establishes baselines for disaster preparedness and home structure flood hazard mitigation, explores household-level ramifications, and examines how preparedness and mitigation relate to health effects, event exposures, and recovery. Between 70 and 80 per cent of participants instituted preparedness measures. Mitigation actions varied: six per cent had interior drainage systems and 83 per cent had elevated indoor heating/cooling components. Sixty per cent reported home damage. One-half highlighted allergies and two-thirds indicated some level of post-traumatic stress (PTS). Three-quarters worried about family members/friends. The results of generalised linear models revealed that greater pre- event mitigation was associated with fewer physical health problems and adverse experiences, lower PTS, and faster recovery. The study design exposed the broad benefits of home structure flood hazard mitigation for households after Harvey.     

Effect of Hunting on the Reproduction of the Sable Population

Russian Journal of Ecology - Analysis of hunting samples of the Kamchatka sable population for 2001–2013 has revealed changes in the reproductive parameters of females over the period from...     

Influence of Chronic Man-made Pollution on Bromus inermis Genome Size

Russian Journal of Ecology - Technogenic pollution can accelerate microevolutionary processes in natural populations. We estimated the nuclear DNA content of 10 Bromus inermis Leyss. samples from...     

Using Ion-Exchange Resins to Study Soil Response to Experimental Watershed Acidification

Ion-exchange resins (IER) offer alternative approaches to measuring ionic movement in soils that may have advantages over traditional approaches in some settings, but more information is needed to understand how IER compare with traditional methods of measurement in forested ecosystems. At the Bear Brook Watershed in Maine (BBWM), one of two paired, forested watersheds is treated bi-monthly with S and N (28.8 and 25.2kgha⁻¹yr⁻¹ of S and N, respectively). Both IER and ceramic cup tension lysimeters were used to study soil solution responses after ∼11 years of treatment. Results from both methods showed treatments resulted in the mobilization of base cations and Al, and higher SO₄—S and inorganic N in the treated watershed. Both methods indicated similar differences in results associated with forest type (hardwoods versus softwoods), a result of differences in litter quality and atmospheric aerosol interception capacity. The correlation between lysimeter and IER data for individual analytes varied greatly. Significant correlations were evident for Na (r=0.75), Al (r=0.65), Mn (r=0.61), Fe (r=0.57), Ca (r=0.49), K (r=0.41) and NO₃—N (r=0.59). No correlation was evident between IER and soil solution data for NH₄—N and Pb. Both IER and soil solution techniques suggested similar interpretations of biogeochemical behavior in the watershed.     

Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.     

A Rapid Method for Assessing the Environmental Performance of Commercial Farms in the Pampas of Argentina

The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators by users. Different procedures were applied to validate the model and present the results to the users. Regression models (based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas. An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g., through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers.     

Comparative Metal Distribution in Hair of Pakistani and Libyan Population and Source Identification by Multivariate Analysis

Using nitric acid-perchloric acid wet digestion based FAAS method ten selected metals (Cd, Co, Cr, Fe, K, Mn, Na, Ni, Pb and Zn) were determined in the scalp hair of male Pakistani and Libyan donors (n = 62), between 3–54 years age and residing in typical urban areas. The study was taken up to identify sources of metal distribution in two diverse population segments exposed to different environments. Sodium emerged with the highest mean hair concentration of 511.0 μg/g and 496.9 μg/g for Libyan and Pakistani donors respectively, followed by K, at 266.2 μg/g and 242.4 μg/g for the two donor categories. Cadmium showed the lowest mean hair concentration for both Pakistani (0.380 μg/g) and Libyan (0.530 μg/g) donors. Levels of Na, K, Pb, Cr and Cd were higher in hair of Libyan donors compared with Pakistani counterparts which showed higher comparative levels of Zn, Fe, Co, Ni and Mn. Strong metal-to-metal correlations were found between Na–K (r = 0.638) and Cd–Co (r = 0.574) for Pakistani donors, while for Libyan donors, Na–K (r = 0.680) and Fe–Mn (r = 0.624) correlations emerged as strongly significant. Only K was found to have a strong positive correlation (r = 0.611) with age for Pakistani donors while this correlation was significantly negative (r = −0.500) for Libyan donors, probably arising from individual food habits. Other metals showed no viable relationship with age. Principal Component Analysis (PCA) and Cluster Analysis (CA) of the data evidenced food, industrial emissions and automobile emissions as possible sources of metal distribution. The results of the present study are compared with those reported for subjects from other regions of the world.