Environmental samples are extremely diverse but share a tendency towards heterogeneity. This poses methodological challenges when investigating biogeochemical processes as large data sets are typically required in order to thoroughly explore the system complexity. Increasingly, the development of analytical tools capable of probing element distribution and speciation at the microscale are allowing this challenge to be addressed. For instance, laterally-resolved synchrotron x-ray fluorescence microscopy (XFM) has become a key method for the in situ investigation of micronutrients and inorganic contaminants in environmental samples. This presentation will demonstrate how recent advances in x-ray fluorescence detector technology are bringing new possibilities for environmental research. State-of-the-art fast detectors such as the CSIRO/BNL Maia detector at the Australian Synchrotron (XFM beamline) are drastically reducing dwell times during scanning. This allows major issues such as x-ray beam damage of hydrated samples to be circumvented. Temporal beamtime requirements are also being reduced with high data rates, zero overheads and short transit times per pixel allowing 2D images to be acquired in minutes rather than hours. This also makes particularly time-consuming techniques such as the collection of 3D data-sets for fluorescence tomography increasingly feasible. The extent of recent developments in hard x-ray fluorescence analysis of environmental samples will be demonstrated using recently collected Megapixel µXRF maps of contaminant distribution in biosolids. Tomographic data documenting the internal elemental distribution of contaminants in fresh hydrated plant roots will also be presented. Micro-XRF tomography, involving the collection of a ‘rotation series’ of two-dimensional projections of the specimen, has not been widely used to date in environmental research due to issues associated with slow data acquisition times and poor detector efficiency. Clearly, environmental applications of hard x-ray fluorescence mapping are set to grow as the advent of fast detectors facilitates deployment of increasingly powerful µ-XRF mapping techniques.