Prioritising local action for water quality improvement using citizen science; a study across three major metropolitan areas of China.

Streams in urban areas are prone to degradation. While urbanization-induced poor water quality is a widely observed and well documented phenomenon, the mechanism to pinpoint local drivers of urban stream degradation, and their relative influence on water quality, is still lacking. Utilizing data from the citizen science project FreshWater Watch, we use a machine learning approach to identify key indicators, potential drivers, and potential controls to water quality across the metropolitan areas of Shanghai, Guangzhou and Hong Kong.

Assessing metal pollution in ponds constructed for controlling runoff from reclaimed coal mines.

Constructing ponds to protect downstream ecosystems is a common practice in opencast coal mine reclamation. As these ponds remain integrated in the landscape, it is important to evaluate the extent of the effect of mine pollution on these ecosystems. However, this point has not been sufficiently addressed in the literature.