Many biological systems are comprised of active particles, that is entities which move by consuming energy from their environment such as flocks of fish, cell tissues or bacterial swarms. The interaction of active particles with each other or complex environments, such as porous media and chemical fields, leads to behaviour unlike that of classical equilibrium systems. The present thesis is concerned with the theoretical and experimental investigation of the transport behaviour of active particles to elucidate how it results from their environmental interactions. To investigate the impact of different boundary conditions, I studied the diffusive transport of Active Brownian Particles (ABP) in an obstacle lattice using agent-based simulations. These show that boundary conditions which preserve the particle’s orientation can result in high diffusivities even at high obstacle densities, unlike classical specular reflection. The dynamics are well described by a model based on Run-and-Tumble particles (RTP) with microscopically derived parameters. The study was then extended to investigate the transport of RTP in structured environments in presence of chemical gradients, which bias the active particles in a process termed chemotaxis. Results of this model show how the reduction of chemotaxis in obstacle lattices depends on the boundary condition. To complement theoretical analysis, I investigated bacterial scattering experimentally by tracking wild-type and smooth-swimming mutants of the model bacterium Escherichia coli swimming in microfluidic channels with lattices of obstacles. Based on the microscopic analysis of scattering events, the diffusive transport was modelled and compared to the experimental measurements. In a final investigation, I considered how heterogeneities in the environment affect active particle transport. As non-classical surface interactions reduce the effective speed at obstacles, introducing a non-homogenous distribution of obstacles can introduce a spatial dependence of the swimming speed. Combining simulations and preliminary experiments, I show that this introduces a drift towards denser obstacle regions. A spatially varying speed can also be introduced directly by bacteria via chemokinesis, which is a change in swimming speed according to the absolute level of a chemical. I extend a Keller-Segel type model to include chemokinesis and apply it to predict the dynamics of bacterial populations in experimentally inspired chemical fields. I find that chemokinesis can not only enhance the chemotactic population response, but also modifies it qualitatively.