In this study, two methods including data envelopment analysis (DEA) and life cycle assessment (LCA) were applied in order to determine energy efficiency and aid in the reduction of environmental burdens for tea production in Guilan province, Iran. The initial data were collected from 30 tea producers using a face-to-face questionnaire. Two models including constant return to scale (CCR) and variable return to scale (BCC) were used for calculating efficiency scores. Simultaneously, ten impact categories (AD, AC, EP, GW, OLD, FE, ME, HT, TE, and PO) were assessed to identify the main problem areas in the tea farms. The results indicated that the average technical efficiency, pure technical efficiency and scale efficiency were 0.881, 0.979, and 0.897, respectively. Moreover, the total energy saving was computed to be in the range of 7193MJha(-1). The highest share of total energy saving potential belonged to nitrogen with 65.93% observed. Based on the results, nitrogen, diesel fuel and machinery were the main hotspots in the majority of impact categories in both of present and DEA farms. Furthermore, in this study, the potential for impact category reduction was investigated and the results illustrated that between 17 and 20% of emissions can be reduced by converting present to DEA farms. In conclusion, the joint DEA+LCA method can improve the energy efficiency and environmental impacts in tea production, significantly. (C) 2017 American Institute of Chemical Engineers