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China is experiencing an enormous increase in municipal household solid waste (MHSW) generation and is facing multiple problems associated with the treatment of MHSW. This paper analyses factors affecting residents’ satisfaction with MHSW treatment performance. Six factors were identified by the Delphi method: (a) pick-up frequency by waste collection vehicles, (b) fund supply situation, (c) charging standard for waste treatment, (d) waste bin arrangement, (e) laws and regulations, (f) publicity and education. We examine the significance of these six influencing factors, estimating binary logistic regression models. Data for this study are derived from the survey responses of 469 households in Harbin, one of the largest cities in northeast China. The results indicate that ‘pick-up frequency by waste collection vehicles’ is ranked the first and most important determinant of Harbin residents’ satisfaction with MHSW treatment; this is closely followed by ‘publicity and education’. The third and fourth significant influencing factors, respectively, are ‘fund supply situation’ and ‘charging standard for waste treatment’. The last two factors are ‘laws and regulations’ and ‘waste bin arrangement’. By understanding the influence of various factors on residents’ satisfaction, this study aims to help in designing an effective waste management system to reduce the cost of MHSW management, and to raise the residents’ satisfaction with municipal solid waste treatment. Based on the research findings, we advocate that establishing a reasonable waste transport (pick-up) system as well as strengthening publicity and education of waste management are key to improving residents’ satisfaction with the MHSW treatment performance.

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem‐mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best‐explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad‐leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

Estimation of tree biomass is an essential part of studies on carbon sequestration and cycling in forest ecosystem. Small trees grow in the understory and allometric development is different from that of mature trees. However, less attention has been paid to biomass estimates of small trees, especially in mixed forest where tree competition is intensive. Tree allometric equations at both branch level and at whole tree level were, thus, developed and compared for the small trees of Korean pine (Pinus koraiensis) in a mixed stand in northeastern China. At branch level, the best model for live branch biomass was one which used a combination of branch diameter, branch length, whorl position and relative branch depth. For needle biomass, the best model did not significantly improve the estimate with more variables. At whole tree level, stem diameter at breast height (DBH) was a significant determinant of biomass for different components. Tree height did not significantly improve biomass estimation at all. Tree crown variables proved to be useful for estimating all biomass components except the fine roots. The variable measuring aboveground competition intensity was a significant negative determinant of biomass components except canopy biomass. Comparisons to published equations for the same species growing in Heilongjiang province in northeastern China and in central South Korea, were also presented. Both total aboveground biomass and belowground biomass in our study showed somewhat smaller values for a given diameter than the trees growing in other two places.