温室气体
环境科学
无组织排放
填埋气
甲烷
遥感
废物管理
环境工程
时间分辨率
工程类
工艺工程
数据收集
全球变暖
堆肥
环境影响评价
度量(数据仓库)
空气污染
温室效应
计算机科学
环境监测
清洁生产
气候变化
作者
Dennis Dika Dankwa,Michael Yongha Boh,O. Grant Clark
标识
DOI:10.1016/j.wasman.2025.115250
摘要
Composting is an important way of diverting municipal organics from landfills to reduce methane emissions. However, compost production is a source of greenhouse gas emissions (GHGs). To develop emissions mitigation strategies, methods to accurately measure GHGs from composting are needed. A systematic review of techniques for measuring GHGs from composting was carried out to evaluate different methodologies and their suitability for various applications. A literature search was performed using the Web of Science and Scopus databases to find information about different measurement methods used during composting from 2014 to 2024. Of the measurement methods identified, the static chamber method was the most widely applied due to its simplicity and cost-effectiveness, but it provides limited spatial representation and can disrupt emissions. Dynamic chambers and micrometeorological techniques give superior temporal resolution but are complex and costly. Emerging technologies, such as automated chambers and remote sensors on unmanned aerial vehicles and satellites, can potentially provide scalable, high-resolution data, but cost, high detection thresholds, and environmental interference present challenges. In this review, approaches for improving existing measurement techniques and the importance of developing standardized methodologies for measuring GHGs during composting have been spotlighted. To improve measurement accuracy and data quality, future research should focus on developing low-cost, automated chambers with large footprints and combining multiple technologies for data cross-validation. This should enable researchers and waste management practitioners to make guided decisions on methods that increase measurement accuracy, which will lead to the development of strategic policies to reduce emissions and fight against climate change.
科研通智能强力驱动
Strongly Powered by AbleSci AI