Circular Economy and the Changing Geography of International Trade in Plastic Waste.

Plastic pollution has become a major environmental concern worldwide. As the circular economy is increasingly seen as a means for achieving sustainable development, it is imperative to promote the more efficient use of plastics worldwide. An integral part of the circular economy model, trade in waste, and the scrap for recovery is a part of the solution to achieve sustainability. This paper studies the changing geography of the international trade in plastic waste. It reveals increasingly complex patterns of the transboundary trade in plastic waste over more than two decades. The movement of plastic waste from high-income countries to developing nations has been the largest flow, but trade flows of other directions turn out to be significant. The findings of the paper debunk the North-South or core-periphery dichotomy that is embedded in the international environment justice tradition (including the ecologically unequal exchange theory) as well as in international environmental regulatory regimes such as the Basel Convention. The paper contributes to the discussions about value that are central in political economic approaches to global trade (e.g., the global value chain and global production network) by demonstrating the relative, spatial, and dynamic nature of the concept. As the transboundary trade in plastic waste has exacerbated pollution and marine litter in some major receiving countries, it needs to be better monitored and regulated to ensure it is conducted in a transparent and environmentally sound manner. The paper also explores several policy measures that could help tackle the plastic pollution crisis and achieve sustainable development.

Spatial characteristics and influencing factors of river pollution in China.

Based on recent water quality data collected from 763 monitoring sections nationwide, this study examined the concentration of major pollutants in China's major rivers. A spatial autocorrelation analysis confirmed that river pollution was spatially uneven and clustered. While pollution of surface water was a nationwide concern, most serious water pollution happened in the Huai, Hai, Yellow, and Liao river Basins in Northern China. The results of the spatial regression analysis showed that GDP per capita, surface water stock, population, and economic structure were all significantly correlated with surface water pollution, with population having strongest impact, followed by level of economic development. By investigating the common characteristics shared by the "hotspot" cities where serious water pollution occurred, this study recommended a regional or basin approach to assessing water quality and controlling river pollution that cuts across jurisdiction boundaries. While China has made considerable progress in improving water productivity, there is still enormous potential in water conservation. It is also imperative to restructure local economy and develop water-efficient, less polluting industries and services. PRACTITIONER POINTS: River pollution in China was spatially uneven and clustered. Most serious water pollution happened in the Huai, Hai, Yellow, and Liao river basins in Northern China. GDP per capita, surface water stock, population, and economic structure correlated with surface water pollution, with population having strongest impact. A regional or basin approach was recommended to assess water quality and controlling river pollution across jurisdiction boundaries. It is also imperative to restructure local economy and develop water-efficient, less polluting industries and services.

A Spatiotemporal Analysis of Schistosomiasis in Hunan Province, China.

Based on annual parasitological data recently collected at county and village levels, this article presents a multiscale spatiotemporal analysis of transmission risk of schistosomiasis japonica in Hunan Province during 2001 to 2015 in a geographic information system environment. The study shows that the incidence and prevalence rate of human Schistosoma japonicum infection in Hunan Province decreased after 2001. A spatial autocorrelation analysis reveals the existence of spatial clusters of human Schistosoma japonicum infection and a growing tendency of spatial clustering over time. The identification of high-risk areas (hot spots) helps find areas of priority for future implementation of control strategies. The research demonstrates the importance of spatial scale in public health studies.