Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.

Energy models for demand forecasting—A review

Changing patterns of infectious disease

Due to alarming increase in population and rapid industrialization, drinking water quality is being deteriorated day by day in Pakistan. This review sums up the outcomes of various research studies conducted for drinking water quality status of different areas of Pakistan by taking into account the physicochemical properties of drinking water as well as the presence of various pathogenic microorganisms. About 20% of the whole population of Pakistan has access to safe drinking water. The remaining 80% of population is forced to use unsafe drinking water due to the scarcity of safe and healthy drinking water sources. The primary source of contamination is sewerage (fecal) which is extensively discharged into drinking water system supplies. Secondary source of pollution is the disposal of toxic chemicals from industrial effluents, pesticides, and fertilizers from agriculture sources into the water bodies. Anthropogenic activities cause waterborne diseases that constitute about 80% of all diseases and are responsible for 33% of deaths. This review highlights the drinking water quality, contamination sources, sanitation situation, and effects of unsafe drinking water on humans. There is immediate need to take protective measures and treatment technologies to overcome unhygienic condition of drinking water supplies in different areas of Pakistan.

/pdf/drinking-water-quality-status-and-contamination-in-pakistan-824qm0c2se.pdf

Drinking Water Quality Status and Contamination in Pakistan.

Fresh water accounts for 3% of water resources on the Earth. Human and industrial activities produce and discharge wastes containing heavy metals into the water resources making them unavailable and threatening human health and the ecosystem. Conventional methods for the removal of metal ions such as chemical precipitation and membrane filtration are extremely expensive when treating large amounts of water, inefficient at low concentrations of metal (incomplete metal removal) and generate large quantities of sludge and other toxic products that require careful disposal. Biosorption and bioaccumulation are ecofriendly alternatives. These alternative methods have advantages over conventional methods. Abundant natural materials like microbial biomass, agro-wastes, and industrial byproducts have been suggested as potential biosorbents for heavy metal removal due to the presence of metal-binding functional groups. Biosorption is influenced by various process parameters such as pH, temperature, initial concentration of the metal ions, biosorbent dose, and speed of agitation. Also, the biomass can be modified by physical and chemical treatment before use. The process can be made economical by regenerating and reusing the biosorbent after removing the heavy metals. Various bioreactors can be used in biosorption for the removal of metal ions from large volumes of water or effluents. The recent developments and the future scope for biosorption as a wastewater treatment option are discussed.

/pdf/application-of-biosorption-for-removal-of-heavy-metals-from-2wwi5v412f.pdf

Application of Biosorption for Removal of Heavy Metals from Wastewater

An assessment of groundwater quality for irrigation and drinking purposes around brick kilns in three districts of Balochistan province, Pakistan, through water quality index and multivariate statistical approaches

Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan

One of the detailed and useful ways to develop land use classification maps is use of geospatial techniques such as remote sensing and Geographic Information System (GIS). It vastly improves the selection of areas designated as agricultural, industrial and/or urban sector of a region. In Islamabad city and its surroundings, change in land use has been observed and new developments (agriculture, commercial, industrial and urban) are emerging every day. Thus, the rationale of this study was to evaluate land use/cover changes in Islamabad from 1992 to 2012. Quantification of spatial and temporal dynamics of land use/cover changes was accomplished by using two satellite images, and classifying them via supervised classification algorithm and finally applying post-classification change detection technique in GIS. The increase was observed in agricultural area, built-up area and water body from 1992 to 2012. On the other hand forest and barren area followed a declining trend. The driving force behind this change was economic development, climate change and population growth. Rapid urbanization and deforestation resulted in a wide range of environmental impacts, including degraded habitat quality.

/pdf/dynamics-of-land-use-and-land-cover-change-lulcc-using-295bezwjaa.pdf

Dynamics of land use and land cover change (LULCC) using geospatial techniques: a case study of Islamabad Pakistan.

Monitoring urban transport air pollution and energy demand in Rawalpindi and Islamabad using leap model

Microorganisms play an important role in the bioremediation of heavy metal-contaminated wastewater and soil. In this research, isolation of heavy metal-resistant fungi was carried out from wastewater-treated soil samples of Hudiara drain, Lahore. The purpose of the present investigation was to observe fungal absorption behavior toward heavy metal. The optimum pH and temperature conditions for heavy metal removal were determined for highly tolerant isolates of Aspergillus spp. along with the initial metal concentration and contact time. Biosorption capacity of A. flavus and A. niger was checked against Cu(II) and Pb(II), respectively. The optimal pH was 8–9 for A. flavus and 4–5.4 for A. niger, whereas optimal temperature was 26 and 37 °C, respectively. Moreover, the biosorption capacity of A. flavus was 20.75–93.65 mg g−1 for Cu(II) with initial concentration 200–1400 ppm. On the other hand, biosorption capacity of A. niger for Pb(II) ranged from 3.25 to 172.25 mg g−1 with the same range of initial metal concentration. It was also found that equilibrium was maintained after maximum adsorption. The adsorption data were then fitted to Langmuir model with a coefficient of determination >0.90. The knowledge of the present study will be helpful for further research on the bioremediation of polluted soil.

Rabia Shabbir

Papers

Land use change mapping and analysis using Remote Sensing and GIS: A case study of Simly watershed, Islamabad, Pakistan

Dynamics of land use and land cover change (LULCC) using geospatial techniques: a case study of Islamabad Pakistan.

Monitoring urban transport air pollution and energy demand in Rawalpindi and Islamabad using leap model

Biosorption and Bioaccumulation of Copper and Lead by Heavy Metal-Resistant Fungal Isolates

Water resource vulnerability assessment in Rawalpindi and Islamabad, Pakistan using Analytic Hierarchy Process (AHP)