This　paper　is　concerned　with　the　event-triggered　model　predictive　control　(ETMPC)　problem　of　nitrogen　removal　process　in　the　wastewater　treatment　plants.　The　main　objective　of　this　paper　is　to　design　an　event-triggered　control　strategy　such　that　the　computation　burden　can　be　reduced　effectively　while　maintaining　the　desired　system　performance.　Unlike　existing　model　predictive　control　(MPC),　the　controller　in　the　proposed　ETMPC　takes　action　when　certain　event　conditions　are　satisfied,　and　thus　can　reduce　the　communication　and　computation　resource　caused　by　continuous　controller　update.　The　triggering　condition　is　designed　according　to　the　system　output　error　and　the　prediction　step　of　the　MPC　controller,　and　thus　is　easy　to　check.　Moreover,　a　state　space　model　of　the　studied　nitrogen　removal　process　is　built,　based　on　which　the　ETMPC　is　designed.　The　controller　is　developed　to　maintain　the　tracking　performance　of　the　dissolved　oxygen　concentration　and　nitrate　nitrogen　concentration　by　adjusting　two　key　variables　in　the　WWTPs.　The　stability　analysis　of　the　closed-loop　system　under　the　designed　control　strategy　is　conducted　by　using　the　Lyapunov　stability　theory.　Some　simulations　are　conducted　to　verify　the　effectiveness　of　the　proposed　method.　Simulation　results　show　that　the　proposed　method　can　greatly　reduce　the　number　of　controller　update　by　up　to　60%　compared　with　MPC,　whereas　the　ISE　only　increases　by　about　0.1,　which　is　acceptable　for　WWTPs.