Some options you may wish to consider:
- If you are looking for identifying a significant difference, a Statistical Process Control (SPC) chart using Western Electric rules might also help you identify that it is occurring. As @IrishStat has suggested, graphing the difference between the two time series is the best start. Then applying SPC rules based on analysis of a stable period of the two time series is good.
- A more detailed pragmatic approach is chronostatistics that is gathering wide acceptance in the mining industry for identifying change and the specific characteristics of noise in time series data. As you can imagine, in an environment where you are interested in 0.001% of the material, uncertainty in the sampling and variability of the process must be understood to know if you have a difference in two time series.
As a mine process engineer, I am used to dealing with time series data that is a lot more noisy than this and chronostatistics (proponents include Pierre Gy and Francis Pitard) allows identification of the errors introduced by the data sampling technique and other aspects of data gathering. More accessible papers (i.e. easier for non-professional statisticians) have been written by Tim Napier-Munn who has a very application-based approach to assessing time series data.
I am not aware of any open source papers but both of these authors have published through Elsevier.