A novel computationally efficient machine learning (ML) framework has been developed for
constructing the turbulent flow field of single-phase or two-phase particle-liquid flows in a …

Purpose The quality of construction projects is mainly dependent on the process quality
during the construction phase than product quality. The key factors that influence the …

One aim of roadside green infrastructure (GI) is to mitigate exposure to local, traffic-
generated pollutants. Here, we determine the efficacy of roadside GI in improving local air …

Precipitation regimes in terms of magnitude, intensity, and frequency have a direct and
immediate impact on the occurrence of landslides. Kashmir Himalaya is a hotspot of …

The present study intends to assess the climatic controls on the streamflow and its impacts
on the changing form of hydrological extremes in the Jhelum basin. The study entails robust …

We report the characterization of anthropogenic magnetic particulate matter (MPM) collected
on leaves from roadside Callistemon (bottlebrush) trees from Lahore, Pakistan, and on …

Abstract Snowmelt Runoff Model (SRM) was employed to study the impact of climate change
on the hydrology of the Sindh basin. The model was calibrated for the year 2010 and …

Particulate matter (PM) concentration levels in the London Underground (LU) are higher
than London background levels and beyond World Health Organization (WHO) defined …

Deterministic models of complex flows are challenging and computationally expensive. We
propose here, for the first time, a computationally efficient data-driven Lagrangian stochastic …

A computationally efficient Lagrangian stochastic model driven by short 3D experimental
trajectories determined by a technique of positron emission particle tracking, has been …