摘要
生活垃圾受到社会经济因素驱动,其理化性质不断变化,并影响垃圾收运处理设施的建设规模和运行参数。大多城市缺少持续数十年的监测统计资料,国内外文献较少报道垃圾理化性质的历史演变及预测研究。在回顾1990—2018年上海生活垃圾理化性质的长时间序列数据基础上,建立了灰色预测与径向基函数(BRF)神经网络模型,预测上海2019—2030年的生活垃圾理化性质,并与国内外30个城市比较。结果表明:(1)近30年来上海生活垃圾厨余类占比(基于干基总固体质量计算)从82.72%降低至54.78%,纸类和橡塑类占比上升;容重和含水率呈下降趋势,而低位发热量则表现为明显上升趋势。(2)人均国内生产总值(GDP)是关键影响因素,与厨余类占比呈负相关性,而与纸类和橡塑类占比呈正相关性。(3)在垃圾不分类情景下,上海2019—2030年的厨余类占比将从52.74%下降至44.24%,纸类和橡塑类占比呈上升趋势。在垃圾分类情景下,纸类和橡塑类占比将分别上升至37.20%和44.67%。此外,预测结果与基于上海和国内外城市混合数据的预测值具有较好的一致性。研究结果对全国新一轮生活垃圾的分类、收运、处理处置规划具有参考价值。
Municipal solid waste(MSW)is driven by socio-economic factors,and its physicochemical characteristics are changing over time,which will affect the capacity and operation parameters of waste collection and disposal facilities.Due to the lack of monitoring statistics in recent decades,the historical change and prediction of the physicochemical characteristics of MSW were rarely reported in literatures.Based on the long-term series data in Shanghai from 1990 to 2018,this study established a grey prediction and RBF neural network model to predict the physicochemical characteristics of MSW from 2019 to 2030,and it was compared with 30 domestic and foreign cities.The results showed that:(1)the percentage(based on total solid mass)of kitchen waste decreased from 82.72%to 54.78%in the past 30 years,while that of waste paper and rubber-plastic increased;the bulk density and moisture content showed a downward,and the low calorific value displayed a obvious upward trend.(2)Per capita GDP was one of the key drivers,which was negatively correlated with the percentage of kitchen waste,while positively correlated with waste paper and rubber-plastic.(3)In the mixed waste scenario,the percentage of kitchen waste in Shanghai would decrease from 52.74%to 44.24%from 2019 to 2030,while that of waste paper and rubber-plastic would increase.In the separated waste scenario,waste paper and rubber-plastic would rise to 37.20%and 44.67%respectively.In addition,the modeling results could well agree with the prediction values based on mixed data of Shanghai and domestic and foreign cities.The results in this paper could be referenced for the collection,transportation and disposal of MSW in China.
作者
葛佳音
吴冰思
单福征
贾悦
黄景能
姚沛帆
刘艺璇
赵军
钱光人
GE Jiayin;WU Bingsi;SHAN Fuzheng;JIA Yue;HUANG Jingneng;YAO Peifan;LIU Yixuan;ZHAO Jun;QIAN Guangren(School of Environmental and Chemical Engineering,Shanghai University,Shanghai 200444;Shanghai Environmental Sanitation Engineering Design Institute Co.,Ltd.,Shanghai 200232)
出处
《环境污染与防治》
CAS
CSCD
北大核心
2023年第9期1195-1201,1207,共8页
Environmental Pollution & Control
基金
国家重点研发计划“固废资源化”重点专项(No.2018YFC1900700)
上海市2022年度“科技创新行动计划”科技支撑碳达峰碳中和专项(No.22dz1209004)。
关键词
生活垃圾
影响因素
理化性质
径向基函数神经网络
预测
municipal solid waste
influencing factors
physicochemical characteristics
RBF neural network
prediction
