We prove a characterization of Pareto variable based on quantiles when conditional distribution above a threshold is considered. A similar characterization for exponential distribution is also obtained. The results are extended to discretized random variables. For some well known distributions, effect of conditioning the variable crossing a threshold on quantiles is investigated. The results are further extended to bivariate exponential and bivariate Pareto type models which are relevant to explain lifestyle data. Applications of the results are made in estimation of conditional quantiles in environmental data. Pareto model for excess of flood-peaks of a river seems to be satisfactory with high threshold values. Applications are also made on Yam-yield, wind speed data of high energy due to extratropical cyclones in coastal regions and worldwide earth-tremor data.