A meta-analysis of heavy metals pollution in farmland and urban soils in China over the past 20 years

Causal attribution of recent biological trends to climate change is complicated because non-climatic influences dominate local, short-term biological changes. Any underlying signal from climate change is likely to be revealed by analyses that seek systematic trends across diverse species and geographic regions; however, debates within the Intergovernmental Panel on Climate Change (IPCC) reveal several definitions of a 'systematic trend'. Here, we explore these differences, apply diverse analyses to more than 1,700 species, and show that recent biological trends match climate change predictions. Global meta-analyses documented significant range shifts averaging 6.1 km per decade towards the poles (or metres per decade upward), and significant mean advancement of spring events by 2.3 days per decade. We define a diagnostic fingerprint of temporal and spatial 'sign-switching' responses uniquely predicted by twentieth century climate trends. Among appropriate long-term/large-scale/multi-species data sets, this diagnostic fingerprint was found for 279 species. This suite of analyses generates 'very high confidence' (as laid down by the IPCC) that climate change is already affecting living systems.

The presence of outliers and influential cases may affect the validity and robustness of the conclusions from a meta-analysis. While researchers generally agree that it is necessary to examine outlier and influential case diagnostics when conducting a meta-analysis, limited studies have addressed how to obtain such diagnostic measures in the context of a meta-analysis. The present paper extends standard diagnostic procedures developed for linear regression analyses to the meta-analytic fixed- and random/mixed-effects models. Three examples are used to illustrate the usefulness of these procedures in various research settings. Issues related to these diagnostic procedures in meta-analysis are also discussed. Copyright © 2010 John Wiley & Sons, Ltd.

Heavy metal pollution has pervaded many parts of the world, especially developing countries such as China. This review summarizes available data in the literature (2005-2012) on heavy metal polluted soils originating from mining areas in China. Based on these obtained data, this paper then evaluates the soil pollution levels of these collected mines and quantifies the risks these pollutants pose to human health. To assess these potential threat levels, the geoaccumulation index was applied, along with the US Environmental Protection Agency (USEPA) recommended method for health risk assessment. The results demonstrate not only the severity of heavy metal pollution from the examined mines, but also the high carcinogenic and non-carcinogenic risks that soil heavy metal pollution poses to the public, especially to children and those living in the vicinity of heavily polluted mining areas. In order to provide key management targets for relevant government agencies, based on the results of the pollution and health risk assessments, Cd, Pb, Cu, Zn, Hg, As, and Ni are selected as the priority control heavy metals; tungsten, manganese, lead-zinc, and antimony mines are selected as the priority control mine categories; and southern provinces and Liaoning province are selected as the priority control provinces. This review, therefore, provides a comprehensive assessment of soil heavy metal pollution derived from mines in China, while identifying policy recommendations for pollution mitigation and environmental management of these mines. © 2013.