4.7 Article

Anaerobic digestion of lignocellulosic waste: Environmental impact and economic assessment

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 231, 期 -, 页码 352-363

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2018.10.020

关键词

Anaerobic digestion; Lignocellulosic waste; Environmental impact; Cost optimal

资金

  1. EU by Czech Republic Operational Programme Research and Development, Education, Priority 1: Strengthening capacity for quality research [CZ.02.1.01/0.0/0.0/15_003/0000456]
  2. Universiti Teknologi Malaysia (UTM), Johor Bahru
  3. University of Manchester, UK

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Lignocellulosic waste (LW) is abundant in availability and is one of the suitable substrates for anaerobic digestion (AD). However, it is a complex solid substrate matrix that hinders the hydrolysis stage of anaerobic digestion. This study assessed various pre-treatment and post-treatments of lignocellulosic waste for anaerobic digestion benefiting from advanced P-graph and GaBi software (Thinkstep, Germany) from the perspective of cost and environmental performances (global warming potential, human toxicity, ozone depletion potential, particulate matter, photochemical oxidant creation, acidification and eutrophication potential). CaO pre-treatment (P4), H2S removal with membrane separation post-treatment (HSR MS) and without the composting of digestate is identified as the cost-optimal pathway. The biological (P7- Enzyme, P8- Microbial Consortium) and physical (P1- Grinding, P2- Steam Explosion, P3- Water Vapour) pre-treatments alternatives have lower environmental impacts than chemical pre-treatments (P4- CaO, P5- NaOH, P6- H2SO4) however they are not part of the near cost optimal solutions. For post-treatment, the near cost optimal alternatives are H2S removal with organic physical scrubbing (HSR OPS) and H2S removal with amine scrubbing (HSR AS). HSR AS has a better performance in the overall environmental impacts followed by HSR MS and HSR OPS. In general, the suggested cost-optimal solution is still having relatively lower environmental impacts and feasible for implementation (cost effective). There is very complicated to find a universal AD solution. Different scenarios (the type of substrate, the scale, product demand, policies) have different constraints and consequently solutions. The trade-offs between cost and environment performances should be a future extension of this work.

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