Aerated irrigation has been proven to increase crop production and quality, but studies on its environmental impacts are sparse.  The effects of aeration and irrigation regimes on soil CO₂ and N₂O emissions in two consecutive greenhouse tomato rotation cycles in Northwest China were studied via the static closed chamber and gas chromatography technique.  Four treatments, aerated deficit irrigation (AI1), non-aerated deficit irrigation (CK1), aerated full irrigation (AI2) and non-aerated full irrigation (CK2), were performed.  The results showed that the tomato yield under aeration of each irrigation regime increased by 18.8% on average compared to non-aeration, and the difference was significant under full irrigation (P<0.05).  Full irrigation significantly increased the tomato yield by 23.9% on average in comparison to deficit irrigation.  Moreover, aeration increased the cumulative CO₂ emissions compared to non-aeration, and treatment effects were significant in the autumn-winter season (P<0.05).  A slight increase of CO₂ emissions in the two seasons was observed under full irrigation (P>0.05).  There was no significant difference between aeration and non-aeration in soil N₂O emissions in the spring-summer season, whereas aeration enhanced N₂O emissions significantly in the autumn-winter season.  Furthermore, full irrigation over the two seasons greatly increased soil N₂O emissions compared to the deficit irrigation treatment (P<0.05).  Correlation analysis indicated that soil temperature was the primary factor influencing CO₂ fluxes.  Soil temperature, soil moisture and NO₃^– were the primary factors influencing N₂O fluxes.  Irrigation coupled with particular soil aeration practices may allow for a balance between crop production yield and greenhouse gas mitigation in greenhouse vegetable fields.

To better interpret summer maize stomatal conductance (g_s) variation under conditions of changing water status at different growth stages, three water stress indicators, soil water content (SWC), leaf-air temperature difference (?T) and leaf level water stress index (CWSI_L) were employed in Jarvis model, which were J_S, J_T and J_C models respectively.  Measurements of g_s were conducted in a summer maize field experiment during the year 2012–2013.  In the insufficient irrigation experiment, three levels of irrigation amount were applied at four different growth stages of summer maize.  We constructed three scenarios to evaluate the performance of the three water stress indicators for estimating maize g_s in a modified Jarvis model.  Results showed that J_T and J_C models had better simulation accuracy than the J_S model, especially at the late growth stage (Scenario 1) or considering the plant recovery compensation effects (Scenario 2).  Scenario 3 indicated that the more environmental factors were adopted, the better prediction performance would be for J_S model.  While for J_T model, two environmental factors (photosynthesis active radiation (PAR), and vapor pressure deficit (VPD)) seemed good enough to obtain a reliable simulation.  When there were insufficient environmental data, CWSI_L would be the best option.  This study can be useful to understand the response of plant stomatal to changing water conditions and will further facilitate the application of the Jarvis model in various environments.