This research seeks the opportunity to further reduce the minimum GHG emissions achieved by individu-ally operating energy systems in the civic, industrial, and transportation sectors through their integration. Each entity – buildings or industrial plants, is equipped with a set of combined cooling, heating, and pow-er (CCHP) system. At the same time, there is heat and electricity transfer among entities. The integration intends to solve the mismatch between the energy demand and energy provided by the CCHP system, which further increases the operation of the CCHP system and reduces GHG emissions of the entire sys-tem. This research introduces an optimization approach for identifying the optimal design and operation of the integrated system, which provides the maximum GHG emission reduction benefits (represented as GHG emissions reduction percentage (GHGD%)). Compared to existing studies on the integrated system, this research (1) differentiates the temperature of industrial heating demands to ensure feasible heat trans-fer; (2) optimizes production rates of plants to minimize GHG emissions of the entire system; (3) identi-fies the optimal relationship between sizes of entities to maximize GHG emissions reduction percentage of the integrated operation. This research implements an integrated system combining entities with different energy demand patterns to balance the supply and demand of heating and electricity. The civic buildings – a residential building and a supermarket that requires more electricity than heating are combined with industrial plants – a confectionery plant, a brewery, and a bakery plant. The confectionery plant and the brewery require more heating than electricity. The bakery plant is investigated under two situations – higher heating than electricity demand and higher electricity demand than heating demand to explore the impacts of changing the energy demand pattern of an entity on GHG emissions reduction benefits of the integrated system. The research also considers the implementation of electric vehicles in the residential building. Results from the case studies indicate that there exist optimal relative entity sizes that lead to a maximum GHGD% of 17.6%. By optimizing the sizes of entities, the highest GHGD% can be maintained at 15.7% - 17.6%, even when the optimal relative entity sizes cannot be followed or there are changes in the energy demand patterns of entities.