Conflict resilience among community forestry user groups: experiences in Nepal

This paper explores the impact of violent conflict in Nepal on the functioning of community forestry user groups (CFUGs), particularly those supported by the Livelihoods and Forestry Programme, funded by the United Kingdom's Department for International Development (DFID). The key questions are: (i) what explains the resilience of CFUGs operating at the time of conflict?; (ii) what institutional arrangements and strategies allowed them to continue working under conflict conditions?; and (iii) what lessons can be drawn for donor‐supported development around the world? The study contributes to other research on the everyday experiences of residents of Nepal living in a period of conflict. It suggests that CFUG resilience was the result of the institutional set up of community forestry and the employment of various tactics by the CFUGs. While the institutional design of community forestry (structure) was very important for resilience, it was the ability of the CFUGs to support and use it effectively that was the determining factor in this regard.     

Evaluation of the levels and sources of trace elements in urban particulate matter

An assessment of air quality of Belgrade, Serbia, was performed by determining the trace element content in airborne daily PM₁₀ and PM_2.5 samples collected from a central urban area. The ambient concentrations of Zn were the highest in PM_2.5 (1,998.0 ng m⁻³). Multivariate receptor modelling (principal component analysis and cluster analysis) has been applied to determine the contribution of different sources of specific metallic components in airborne particles. The obtained results showed that vehicle traffic and fossil fuel combustion in stationary objects were the main sources of trace metals in Belgrade urban aerosols.     

Estimation of land surface temperature using different retrieval methods for studying the spatiotemporal variations of surface urban heat and cold islands in Indian Punjab

Spatial patterns of land surface temperature (LST), surface urban heat island (SUHI), surface urban cold island (SUCI), and their seasonal variations during January (winter) and September (summer) were analyzed over the three cities of Indian Punjab (Balachaur, Ludhiana and Bathinda) using Landsat 5, 7 and 8 satellite data of the years 1991, 2001, 2011, and 2018. Urban hot spots and Urban Thermal Field Variance Index (UTFVI) were used to measure the ecological environment of these cities. Land surface temperature was retrieved from Landsat satellite data using Plank equation, mono-window algorithm (MWA), single-channel algorithm (SCA), and radiative transfer equation. The LST derived using these algorithms was validated with MODIS-LST product. The relationship between LST derived from Landsat 5, 7 and 8 using the four methods and MODIS-LST product was higher with the SCA algorithm (R²?>?0.75). Land surface temperature was significantly positively correlated with built-up but significantly negatively correlated with vegetation. The surface urban heat intensity was higher during September than January, and it was higher in Ludhiana followed by Bathinda and Balachaur, irrespective of the season. Besides built-up area and population density, soil moisture availability in surrounding rural areas has significant impact on increasing surface urban heat intensity during September than January. The SUCIs were formed in the center of Bathinda city during January 1991, but these were in Ludhiana and Balachaur cities during January 2011. The most critical areas for ecological environment based on UTFVI were identified and the critical UTFVI values (>?0.020) were highest in Bathinda city followed by Balachaur and Ludhiana cities. These results suggest that SUHIs and SUCIs are influenced by seasons and the mitigating plans to counteract the overheating of urban areas should be formulated taking into account soil moisture availability in surrounding rural areas, landscape pattern, seasonal variations, local climatic conditions, urban growth, and development plan etc.

     

Recent innovation in clean conversion technologies,carbon capture and utilization,advance treatment for energy,air, water,biomass and soil for green and sustainable development 2021 (ICheEC 2021)

Environmental Science and Pollution Research -     

Performance analysis and optimization of solar-powered E-rickshaw for environmental sustainability in rural transportation

Environmental Science and Pollution Research - The last mile connectivity through public transport is a challenging task in India. However, according to the Society of Indian Automotive...     

Hg Vapor Emission from Broken Compact Fluorescent Lamps (CFLs) in an Acrylic Chamber

The United States Environmental Protection Agency/Environmental Response Team (US EPA/ERT), in collaboration with St. John's College, Dr. B. R. Ambedkar University, Agra, India, is conducting a study to determine Hg vapor emission rates resulting from broken compact fluorescent lamps (CFLs) in a residential setting. The overall objectives of the study are to determine Hg vapor emission data and provide homeowners with cleanup procedures and disposal options for broken CFLs. Most of the currently available CFLs in the US market are manufactured in China for US companies. Several different types of CFLs were purchased from local stores and their Hg content was determined. Based on previous studies, such as the 2011 study by Singhvi and colleagues, five popular spiral CFLs were selected for emission studies in an acrylic chamber. This study found that Hg vapor emissions from CFLs may be significantly greater than those from beads of liquid Hg with weights comparable to the Hg content of the CFLs. The average 24-hour Hg loss into the atmosphere from CFLs broken on a plastic surface ranged from 0.6% to 22% of the bulb content, while that for CFLs broken on carpet ranged from 2.6% to 28%. Projections for a 12 foot × 9.33 foot × 8 foot (25.4 m³) room based on the chamber measurements in this study indicate that CFL breakage in some household settings may produce 24-hour Hg concentrations above the 2000 Agency for Toxic Substances and Disease Registry (ATSDR) minimum risk level (MRL) of 0.2 μg/m³, for typical air exchange rates. This study also indicates that Hg emission may not be proportional to exposed surface area based on experiments using liquid Hg with different surface areas.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

Experimental investigation of different-shaped microwave-heated potatoes: thermal and quality characteristics analysis for food preservation

Environmental Science and Pollution Research - Food materials are consumed for nutritional purposes in the form of fruits, vegetables, plants, and meat. These contain proteins, carbohydrates, and...     

Effect of compression ratio,nozzle opening pressure,engine load,and butanol addition on nanoparticle emissions from a non-road diesel engine

Currently, diesel engines are more preferred over gasoline engines due to their higher torque output and fuel economy. However, diesel engines confront major challenge of meeting the future stringent emission norms (especially soot particle emissions) while maintaining the same fuel economy. In this study, nanosize range soot particle emission characteristics of a stationary (non-road) diesel engine have been experimentally investigated. Experiments are conducted at a constant speed of 1500 rpm for three compression ratios and nozzle opening pressures at different engine loads. In-cylinder pressure history for 2000 consecutive engine cycles is recorded and averaged data is used for analysis of combustion characteristics. An electrical mobility-based fast particle sizer is used for analyzing particle size and mass distributions of engine exhaust particles at different test conditions. Soot particle distribution from 5 to 1000 nm was recorded. Results show that total particle concentration decreases with an increase in engine operating loads. Moreover, the addition of butanol in the diesel fuel leads to the reduction in soot particle concentration. Regression analysis was also conducted to derive a correlation between combustion parameters and particle number emissions for different compression ratios. Regression analysis shows a strong correlation between cylinder pressure-based combustion parameters and particle number emission.