Unveiling Carbon Emission Attributions along Sale Chains.

Substantial anthropogenic emissions have resulted in serious environmental problems in China. Direct emissions and demand-pulled emissions along the supply chains have been extensively investigated. However, understanding the mechanism of how the sectoral emission is transferred through production activities along the sale chains at different production layers remains a challenge. In this paper, a top-down multilayer emission attribution model is developed to unveil the metabolism of multilayer input-driven emissions. For the first time, a diagramming approach enables the exhaustive depiction of the connections between primary input attributions and final production attributions, which allows accurate reallocation of the emission responsibilities to sectors at different production layers. Individual sale chain paths and supply chain paths have been extracted and ranked according to the contributions of emissions. A four-perspective comparison of sectoral emissions (i.e., direct emissions along sale chains, enabled emissions, direct emissions along the supply chains, and embodied emissions) is assessed. We find that at multiple production layers, sectoral direct emissions along the sale chains differ greatly from direct emissions along the supply chains. By comprehensively considering providers, consumers, and producers within a metabolic system, policy-makers should encourage upstream sectors to improve their cleaner production technologies and downstream sectors to adjust their industrial structures.

Treatment of rural domestic wastewater using multi-soil-layering systems: Performance evaluation, factorial analysis and numerical modeling.

The discharge of wastewater in rural areas without effective treatment may result in contamination of surrounding surface water and groundwater resources. This study explored the wastewater treatment performance of multi-soil-layering (MSL) systems through interactive factorial analysis. MSL systems showed good performances under various operating conditions. The COD and BOD5 removal rates in MSL systems could reach 98.53 and 93.66%, respectively. The performances of MSL systems in TP removal stayed at high levels ranged from 97.97 to 100% throughout the experiments. The NH4+ - N removal rates of the well performed MSL systems reached highest levels ranging from 89.96 to 100%. The TN removal rates of aerated MSL systems ranged from 51.11 to 64.44% after 72 days of operation. The independent effects of bottom submersion, microbial amendment and aeration, as well as most interactions were significant. The performance of MSL systems was mainly affected by bottom submersion and aeration as well as their interactions. Aeration was the most positive factor for the removal of organic matter, TP and NH4+ - N. However, oxygenated environment was unfavorable for NO3- - N removal. In the submerged area with limited oxygen, the microbial transformation of NO3- - N still occurred. A stepwise-cluster inference model was developed for tackling the multivariate nonlinear relationships in contaminant removal processes. The results can help obtain a better understanding of the complicated processes among contaminant removal in MSL systems.