Decision trees have been proposed as a basis for modifying table-based injection to reduce transient particulate spikes during the turbocharger lag period. It has been shown that decision trees can detect particulate spikes in real time. In well-calibrated electronically controlled diesel engines these spikes are narrow and are encompassed by a wider NO spike. Decision trees have been shown to pinpoint the exact location of measured opacity spikes in real time thus enabling targeted PM reduction with near zero NO penalty. A calibrated dimensional model has been used to demonstrate the possible reduction of particulate matter with targeted injection pressure pulses. Post injection strategy optimized for near stoichiometric combustion has been shown to provide additional benefits. Empirical models have been used to calculate emission tradeoffs over the entire FTP cycle. An empirical model-based transient calibration has been used to demonstrate that such targeted transient modifiers are more beneficial at lower engine-out NO levels.