This study aims to determine the trade-off between river pollution and the growth of the economy in the context of India using the concept of Environmental Kuznets Curve (EKC). According to EKC theory, environmental pressure tends to rise faster than income growth in the early stages of economic development and then declines in the later stages with further economic growth. The present study has used the cross-sectional time series data for river pollutants of Biochemical Oxygen Demand (BOD) and Dissolved Hydrogen Ions (PH) across various states of India for the period 1990-1991 to 2005-2006. This study shows why the conventional EKC model is not sufficient to ascertain the declining path of pollution as the economy grows in the second stage. The paper uses the modified EKC theory where the EKC curve is proposed to have 2 turning points. Our results indicated 'tilted-S shaped' relationship which contradicts EKC in the early stages. Most of the regions that were studied have crossed the first turning point but are still to cross the second turning point, which means that there will be an ascent in the pollution level in the future. This calls for more stringent environment policies complementing the desired growth path.

Hedonic valuation, Stagnant streams, High elevation, Q51, Q59,

No abstract

Special observations of visibility were taken from the electrometer tower of the Colaba Observatory, about 50 feet from the ground," with a Bennett visibility meter at seven specified hours between sunrise and sunset, almost daily during November1936 to March 1939. Seven objects situated at different distances in different directions from the observatory were used and the data from these observations are discussed for monthly variations. For hourly observations on selected days' and nights, fourteen objects at different directions and distances and five city lamps towards north, were mainly observed with the Bannett and a Wigand meter. Typical hourly observations are discussed and shown diagrammatically. Wind and associated visibility are statistically analysed.