NAXOS 2018 6th International Conference on Sustainable Solid Waste - PowerPoint PPT Presentation

NAXOS 2018 6th International Conference on Sustainable Solid Waste Management ANALYSIS OF THE ENVIRONMENTAL IMPACT USING THE WASTE REDUCTION ALGORITHM WAR IN POLYPROPYLENE PROCESS PRODUCTION BY APPLYING GRADE TRANSITIONS STRATEGIES Alexis Velásquez ‐ Barrios 1,2 , Cesar Rueda ‐ Duran 1,2 , Enrique Mogollón 1 , Carlos Ariel Cardona 2* 1 Grupo de Investigación en Tecnología de Polimeros, Esenttia Polipropileno del Caribe S.A 2 Instituto de Biotecnología y Agroindustria, Departamento de Ingeniería Química, Universidad Nacional de Colombia sede Manizales 1

CO CONT NTENT About Esenttia S.A Introduction Methodology Results Conclusion References 2

ABOUT ESENTTIA Third Polypropylene producer in Latinoamerica 3

High ‐ density polyethylene (HDPE) Low ‐ density Linear low ‐ density Polyethylene polyethylene polyethylene (LLDPE) (LDPE) Products Polypropylene Homopolymer Compounds Polypropylene Masterbatch Impact Random Black and Copolymer Additives Copolymer White Colors 4

INTR TRODUC ODUCTI TION ON In a polypropylene polymerization process one of the most important quality variable to control is the Melt Flow. • The MFR (melt flow rate) is a measure for the average chain length or molecular weight of a polymer. • The MFR method is based on the relation between average chain length and melt viscosity: short chain PP grades flow more easily than long chain PP grades. Unit is g/10 minutes Depending of the final application the MF can be between 2 to 30. Melt Flow index is a measure of the ease of flow of the melt of a thermoplastic polymer. 5

INTR TRODUC ODUCTI TION ON When it is desirable to change the MF for example from 8 to 12, H 2 Flow is increased too. C3H6 Always it is an objective to optimize the transition Catalyst stage to produce less transition material. PP production Plant 80,00 H2/C3 Ratio Set Point MF 19,0 17,0 70,00 By applying a 15,0 H 2 /C (grH2/Ton PP) 60,00 ramp of H2 MF 13,0 11,0 50,00 Flow it is 9,0 possible to 40,00 7,0 5,0 increase the 30,00 3,0 Melt flow. Transition time: 4 hours 20,00 1,0 6

INTR TRODUC ODUCTI TION ON This paper aims to demonstrate how the optimization of transition times based on the MF management implies a significant (or not ) reduction of plastic waste avoiding a significant impact on the environment. An environmental analysis is made by applying a Waste Reduction Algorithm (WAR) in order to evaluate the impact over the environment of a polypropylene production process applying grade transitions strategies. 7

INTR TRODUC ODUCTI TION ON The transitions could be a potential waste but it depends mostly on the market 8

METHODOL METHODOLOG OGY Typical Polymerization process Production ASPEN PLUS SIMULATION WAR ANALISYS Homopolymer Initially a simulation in ASPEN PLUS is applied for an Homopolymer production Process in a reactor of NOVOLEN Technology. 9

METHODOL METHODOLOG OGY To evaluate the transitions process, the simulation is made considering a change of Melt Flow (MF) passing from 11 to 20. To do this, the flow of H 2 going to the reactor is modified. So, two scenarios are constructed as follow: Table 1: Ta 1: Case Case I. I. 120 120 TM TM (M (Metric ric To Tons) of of tr tran ansitio tion Po Polypropylene Production. oduction. Item Value C 3 Flow (Ton/h) 30 H 2 Flow (gr/h) 2000 Transition time (h) 4 Amount of transition PP (Ton) 120 Table 2: Case II. 240 TM (Metric tons) of Transition Polypropylene Production. Item Value C 3 Flow (Ton/h) 30 H 2 Flow (gr/h) 6200 Transition time (h) 8 Amount of Transition PP (Ton) 240 10

METHODOLOG METHODOL OGY Waste Reduction Algorithm (WAR). Is simply a tool to be used by design engineers to aid in evaluating the environmental friendliness of a process. WAR ANALYSIS This algorithm calculates the potential environmental impact (PEI) of a process, based upon several impact categories. After the ASPEN simulation, The WAR analysis is applied 11

METHODOLOG METHODOL OGY General Impact category Impact Category Measure of impact category Human Toxicity Ingestion LD 50 Inhalation /dermal OSHA PEL Ecological Toxicity Aquatic toxicity Fathead minnow LC 50 Terrestrial toxicity LD 50 Global atmospheric Global Warming potential GWP impact Ozone depletion potential ODP Regional atmospheric Acidification potential AP impacts Photochemical oxidation PCOP potential 12

METHODOL METHODOLOG OGY The input streams and outputs streams for the WAR analysis are shown. Input nput Output Out ut Pro Proces ess Propylene Propane Polypropylene H 2 Propane Residual Catalyst Cocatalyst Residual Cocatalyst Catalyst WAR ANAL WA ANALYSIS SIS 13

METHODOL METHODOLOG OGY INPUT In the WAR algorithm it is important to specify the polypropylene according to the characteristics that are shown in Table 3. Table 3. Polypropylene specifications. Indicator Unit Value GWP kg CO2 eq 2.00 ODP g CFC ‐ 11 eq n/a AP g SO2 eq 6.13 POCP g Ethene eq 0.92 LC50 mg/lt 51.7 LD50 mg/kg 5.000.000 14

ASPEN ASPEN SIM SIMULA LATIO TION RE RESUL SULTS For the WAR analysis the energy requirements for every equipment involved INPUT in the polymerization process is included. This information was obtained from the ASPEN simulation and validated in plant, Table 4. Table 4. Energy requirements for process equipment. Energy requirement [MJ/h] Equipment Case 2 Case 1 CSTR reactor 50075,123 49992,62 Separator 1123,29 1340,79 Pump 121,87 121,86 Distillation column 29116,152 83797,263 Recycle pump 51,26 36,705 Total 80487,695 135289,24 15

ASPEN ASPEN SIM SIMULA LATIO TION RE RESUL SULT: Case Case 1 The mass balance results from the ASPEN simulation is showed. This information is used as an input for the WAR analysis for both cases: Stream Inlet [kg/h] Outlet [kg/h] Compound Propylene H 2 Catalyst Cocatalyst PP product Propane 24782,18 ‐ ‐ ‐ ‐ 548,28 Propylene Propane 124,53 ‐ ‐ ‐ ‐ 124,55 Hydrogen ‐ 2 ‐ ‐ 0,58 ‐ Catalyst ‐ ‐ 1,65 ‐ 1,65 ‐ Cocatalyst ‐ ‐ ‐ 10 9,96 ‐ Polypropylene ‐ ‐ ‐ ‐ 24235,38 ‐ Total 24906,71 2 1,65 10 24247,57 672,83 16

ASPEN ASPEN SIM SIMULA LATIO TION RE RESUL SULT: Case Case 2 The mass balance results from the ASPEN simulation is showed. This information is used as an input for the WAR analysis for both cases: Stream Inlet [kg/h] Outlet [kg/h] Compound Propylene H 2 Catalyst Cocatalyst PP product Propane 24779,84 ‐ ‐ ‐ ‐ 547,43 Propylene Propane 124,52 ‐ ‐ ‐ ‐ 124,72 Hydrogen ‐ 6,2 ‐ ‐ 3,47 ‐ Catalyst ‐ ‐ 1,65 ‐ 1,65 ‐ Cocatalyst ‐ ‐ ‐ 10 9,96 ‐ Polypropylene ‐ ‐ ‐ ‐ 24235,24 ‐ Total 24904,36 6,2 1,65 10 24250,32 672,15 17

WA WAR RE RESUL SULTS PEI: total rate of potential environmental impact from the process studied. Total rate of potential environmental impact values. Value [PEI/h] Indicator Case 1 Case 2 I out 30489,05 30555,38 I gen ‐ 63825,76 ‐ 63825,76 The results let to highlight that the impact generated by the substances entering the system is reduced by the generation of the polypropylene generated, which is a less dangerous material. 18

RE RESUL SULTS The results are shown as Potential Environmental Impact generated (Generated) and total output rate of environmental impact (Out) for the studied processes. The impact is expressed as the PEI per hour. Potential environmental impact per hour [PEI/h] Case 1 Case 2 Indicator Out Generated Out Generated HTPI 5,95 2,12 5,96 2,13 HTPE 0,45 ‐ 6,7 0,457 ‐ 6,69 TTP 5,95 2,12 5,96 2,13 ATP 187 187 188 188 GWP 19,7 19,7 25 25 ODP 2,92E ‐ 05 2,92E ‐ 05 4,91E ‐ 05 4,91E ‐ 05 PCOP 27800 ‐ 66500 27800 ‐ 66500 AP 2470 2470 2530 2530 Total 30489,05 ‐ 63825,76 30555,377 ‐ 63759,43 19

RE RESUL SULTS The results are shown as Potential Environmental Impact generated (Generated) and total output rate of environmental impact (Out) for the studied processes. The impact is expressed as the PEI per hour. Potential environmental impact per hour [PEI/h] Case 1 Case 2 Indicator Out Generated Out Generated HTPI 5,95 2,12 5,96 2,13 HTPE 0,45 ‐ 6,7 0,457 ‐ 6,69 TTP 5,95 2,12 5,96 2,13 ATP 187 187 188 188 GWP 19,7 19,7 25 25 ODP 2,92E ‐ 05 2,92E ‐ 05 4,91E ‐ 05 4,91E ‐ 05 PCOP 27800 ‐ 66500 27800 ‐ 66500 AP 2470 2470 2530 2530 Total 30489,05 ‐ 63825,76 30555,377 ‐ 63759,43 20