The impacts of organizational green culture and corporate social responsibility on employees’ responsible behaviour towards the society

Environmental Science and Pollution Research - Corporate social responsibility (CSR) initiatives and organizational green culture (OGC) play a significant role in developing organizations and...     

Climate change and major crop production: evidence from Pakistan

Environmental Science and Pollution Research - Climatic changes are posing serious threats to crop production and food insecurity across the globe. This study explores the dynamic relationship...     

Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India

Environmental Science and Pollution Research - In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist’s attention across the globe due to its...     

Do risk perceptions and constraints influence the adoption of climate change practices among small livestock herders in Punjab,Pakistan?

Environmental Science and Pollution Research - Climate change is severely damaging the agricultural system of many food producing regions worldwide. Small/subsistent livestock herders are the most...     

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8’s spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82 %, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.     

Enhanced catalytic complete oxidation of 1,2-dichloroethane over mesoporous transition metal-doped γ-Al_2O_3

High-surface-area mesoprous powders of γ-Al2O3 doped with Cu2+, Cr3+, and V3+ions were prepared via a modified sol–gel method and were investigated as catalysts for the oxidation of chlorinated organic compounds. The composites retained high surface areas and pore volumes comparable with those of undoped γ-Al2O3 and the presence of the transition metal ions enhanced their surface acidic properties. The catalytic activity of the prepared catalysts in the oxidation of 1,2-dichloroethane(DCE) was studied in the temperature range of 250–400°C. The catalytic activity and product selectivity were strongly dependent on the presence and the type of dopant ion. While Cu2+- and Cr3+-containing catalysts showed100% conversion at 300°C and 350°C, V3+-containing catalyst showed considerably lower conversion. Furthermore, while the major products of the reactions over γ-alumina were vinyl chloride(C2H3Cl) and hydrogen chloride(HCl) at all temperatures, Cu- and Cr-doped catalysts showed significantly stronger capability for deep oxidation to CO2.     

Life-cycle assessment of municipal solid waste management alternatives with consideration of uncertainty: SIWMS development and application

This paper describes the development and application of the Stochastic Integrated Waste Management Simulator (SIWMS) model. SIWMS provides a detailed view of the environmental impacts and associated costs of municipal solid waste (MSW) management alternatives under conditions of uncertainty. The model follows a life-cycle inventory approach extended with compensatory systems to provide more equitable bases for comparing different alternatives. Economic performance is measured by the net present value. The model is verified against four publicly available models under deterministic conditions and then used to study the impact of uncertainty on Sydney’s MSW management ‘best practices’. Uncertainty has a significant effect on all impact categories. The greatest effect is observed in the global warming category where a reversal of impact direction is predicted. The reliability of the system is most sensitive to uncertainties in the waste processing and disposal. The results highlight the importance of incorporating uncertainty at all stages to better understand the behaviour of the MSW system.