Chemical waste compositions are important for municipal solid waste management, as they determine the pollution potentials from different waste strategies. A representative dataset for chemical characteristics of indi...Chemical waste compositions are important for municipal solid waste management, as they determine the pollution potentials from different waste strategies. A representative dataset for chemical characteristics of individual waste fractions is frequently required to assess chemical waste composition, but it is usually reported in developed countries and not in developing countries. In this study, a dataset for Chinese waste was established through careful data screening and assessment, named as CN dataset. Meanwhile, a dataset for Danish waste（DK dataset） was also summarized based on previous studies. In order to quantitatively evaluate the reliabilities of CN and DK datasets, the chemical waste compositions in four Chinese cities were estimated by utilizing both of them, respectively. It is indicated that the usage of CN datasets led to significantly lower discrepancies from the actual values based on laboratory analysis in most cases. Within the datasets, the moisture contents of food waste, paper, textiles, and plastics, the carbon content of food waste, as well as the oxygen content of plastics would induce significant divergences, which should be paid special attention when gathering the information. In addition, the fractional waste compositions in China showed similar features with other developing countries but differ significantly with developed countries. Thus the above-mentioned conclusions could also be true in other developing countries.展开更多
基金supported by the National Environmental Protection Standard Project(2015-4)the Shanghai Technical Standard Projects(Nos.14DZ0501500,DB31ZB5-15043)
文摘Chemical waste compositions are important for municipal solid waste management, as they determine the pollution potentials from different waste strategies. A representative dataset for chemical characteristics of individual waste fractions is frequently required to assess chemical waste composition, but it is usually reported in developed countries and not in developing countries. In this study, a dataset for Chinese waste was established through careful data screening and assessment, named as CN dataset. Meanwhile, a dataset for Danish waste（DK dataset） was also summarized based on previous studies. In order to quantitatively evaluate the reliabilities of CN and DK datasets, the chemical waste compositions in four Chinese cities were estimated by utilizing both of them, respectively. It is indicated that the usage of CN datasets led to significantly lower discrepancies from the actual values based on laboratory analysis in most cases. Within the datasets, the moisture contents of food waste, paper, textiles, and plastics, the carbon content of food waste, as well as the oxygen content of plastics would induce significant divergences, which should be paid special attention when gathering the information. In addition, the fractional waste compositions in China showed similar features with other developing countries but differ significantly with developed countries. Thus the above-mentioned conclusions could also be true in other developing countries.
