Physical infrastructure,energy consumption,economic growth,and environmental pollution in Pakistan: an asymmetry analysis

Environmental Science and Pollution Research - This study explores the symmetric and asymmetric effects of physical infrastructure on energy consumption, economic growth, and air pollution of...     

Re-evaluating the asymmetric conventional energy and renewable energy consumption-economic growth nexus for Pakistan

Environmental Science and Pollution Research - To understand the nexus between economic growth and energy sources, in this study, we have selected Pakistan and collected data over the period...     

Survey for cotton mealybug, Phenacoccus solenopsis (Tinsley) and its natural enemies

Mealybug was considered to be a minor pest of cotton but it emerged as a major pest in 2006-2007 in North and Central zones. Extensive field surveys conducted in cotton fields during 2007-09 in Haryana, Rajasthan and Punjab in the North zone and Madhya Pradesh, Maharashtra and Gujarat in the Central zone indicated that Phenacoccus solenopsis was the only major species of mealybug recorded on cotton in North as well as Central zones except one location in Gujarat where Fenrrisia virgata Cockerrel was also recorded. Infestation of mealybug at most of the places in North and Central zones ranged from mild (10-20%) to high (40-60%) during 2007 and 2008 but reduced to traces in 2009. Extensive field survey indicated that Aenasius bambawalei Hayat (Chalcidodea: Encyrtidae), an indigenous parasitoid, played a key role in reducing the insect pestinfestation. The parasitoid was first recorded in Delhi in July 2008 and by 2009 it was found in most of the cotton growing districts of North and Central zones. Its natural parasitization on P solenopsis could reach more than 90% at many locations. This is the most successful example of biological control of mealybug. Along with this parasitoid, another parasitoid, Promuscidea unfasciativentris Girault (Chalcidodea: Aphelinidae), was also recorded at most of the locations in smaller proportions.     

Multiple regression analysis in modeling of columnar ozone in Peninsular Malaysia

This study aimed to predict monthly columnar ozone (O₃) in Peninsular Malaysia by using data on the concentration of environmental pollutants. Data (2003–2008) on five atmospheric pollutant gases (CO₂, O₃, CH₄, NO₂, and H₂O vapor) retrieved from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) were employed to develop a model that predicts columnar ozone through multiple linear regression. In the entire period, the pollutants were highly correlated (R?=?0.811 for the southwest monsoon, R?=?0.803 for the northeast monsoon) with predicted columnar ozone. The results of the validation of columnar ozone with column ozone from SCIAMACHY showed a high correlation coefficient (R?=?0.752–0.802), indicating the model’s accuracy and efficiency. Statistical analysis was utilized to determine the effects of each atmospheric pollutant on columnar ozone. A model that can retrieve columnar ozone in Peninsular Malaysia was developed to provide air quality information. These results are encouraging and accurate and can be used in early warning of the population to comply with air quality standards.     

Asymmetric macroeconomic determinants of energy intensity in China: does economic development matter?

Environmental Science and Pollution Research - Previously, several studies have tried to analyze the various determinants of energy intensity for different countries and regions. However, none of...