RESUMEN
Ecological restoration is one of the most feasible ways to mitigate climate change and conserve ecosystems. However, the scope, intensity, effectiveness, and future potential of ecological restoration are restricted by unfavorable environmental conditions, especially limited water resources and complex topography. This paper proposes an assessment framework of ecological restoration potential under the coupled limits of water resources and slope gradient to quantitatively assess ecological restoration potential (ERP) under these two limiting factors. Results indicate that the current vegetation plantation in 20%, 0.19% and 32% areas of China's 31 provinces are larger, equal, and lower than the vegetation threshold permitted by local water resources respectively, which represents about 0.299 billion ha potential for additional restoration area. The ecological restoration potential under the integrated water resources and slope gradient constraints is 0.4 Pg C, less than half (47%) of the potential under the single limit of water resources (0.856 Pg C). However, this potential and China's existing carbon sink capacity related to terrestrial ecosystems is estimated to offset up to 8% of its current carbon dioxide emissions. Ecological restoration programs in areas with slope >5° will require additional economic investment to support Soil and Water Conservation programs, estimated to average about 212 trillion yuan. Succinctly, it is critical to integrate field investigations, process-based assessments and landscape design for sustainable ecological restoration. This work can provide techniques support for quantitative measurement of ecological restoration potential considering multiple limiting factors and guidance for sustainable implementation of ecological restoration programs.
RESUMEN
Controversies on food delivery services environmental impacts have been sparked due to the growth of this economic sector. This study focuses on the environmental impacts generated by packaging waste related to urban food delivery services. In particular, the Python based web-crawling and sample survey methods are used for big data mining, and LCA-based environmental impacts evaluation and Kernel density analysis methods are combined to determine the positioning trend of food delivery service providers and expansion direction of environmental pollution load in Jing-Jin-Ji region (North China). Results indicate that (1) food delivery service packages presently account for a very small proportion (<0.1%) of municipal solid waste (MSW). However, this study also evidences that food packaging accounts for 15.7% of the total MSW generated in this region. Even if this growing market sector might have a relatively low impact, households' lifestyle might affect the results. (2) In terms of consumption quantity, plastic bags are the most used packages, accounting for 35.08%; wooden chopsticks account for 32.21% and plastic boxes account for 27.43%. Among all environmental impact categories resulting from the process of production of packages, greenhouse effect is the most distinct one. Paper boxes generate the most serious environmental pollution. (3) The distribution of environmental pollution loads resulting from food delivery service packages positively correlates with the distribution of food delivery service providers in Jing-Jin-Ji. Shijiazhuang has the highest degree of pollution resulting from food delivery service packages with the interrupt value ratio of 80%, followed by Baoding City and Chengde City, which have the interrupt value ratios of 65.1% and 48.6%, respectively. Finally, as bridges between food delivery service providers and consumers, food delivery service platforms should improve their environmental protection mechanisms. Meanwhile, the government should define a standard concerning food delivery service packages to consolidate the concept of environmental protection in the society to change the ways people consume, in order to achieve a harmonious co-existence between resource utilization and environmental protection.
