Environmental impact assessments of the Three Gorges Project in China: issues and interventions

The paper takes China's authoritative Environmental Impact Statement for the Yangzi (Yangtze) Three Gorges Project (TGP) in 1992 as a benchmark against which to evaluate emerging major environmental outcomes since the initial impoundment of the Three Gorges reservoir in 2003. The paper particularly examines five crucial environmental aspects and associated causal factors. The five domains include human resettlement and the carrying capacity of local environments (especially land), water quality, reservoir sedimentation and downstream riverbed erosion, soil erosion, and seismic activity and geological hazards. Lessons from the environmental impact assessments of the TGP are: (1) hydro project planning needs to take place at a broader scale, and a strategic environmental assessment at a broader scale is necessary in advance of individual environmental impact assessments; (2) national policy and planning adjustments need to react quickly to the impact changes of large projects; (3) long-term environmental monitoring systems and joint operations with other large projects in the upstream areas of a river basin should be established, and the cross-impacts of climate change on projects and possible impacts of projects on regional or local climate considered. © 2013 Elsevier B.V.Xibao Xu, Yan Tan, Guishan Yan

Inter-observer variation in habitat survey data: investigating the consequences for professional practice

Knowledge of the extent and distribution of vegetation types is essential to underpin conservation assessments, land-use planning and management of wildlife populations (Hill et al. 2005; IEEM 2006; Morris and Thrivel 2009). Despite improvements in remote sensing of land cover, field survey remains an essential method for collection of data on the distribution of habitats and their floristic composition (IEEM 2006). Surveying of vegetation is recognised as a key skill required by ecologists and environmental managers (IEEM 2007, 2011), but studies of variability between surveyors have often revealed significant levels of disagreement in terms of the plant species and habitats recorded (e.g. Scott and Hallam 2002; Milberg et al. 2008; Stevens et al. 2004; Hearn et al. 2011). For example, a study using the National Vegetation Classification (NVC) in the UK found that pairwise spatial agreement between seven surveyors mapping vegetation at the same site averaged only 34% at the community level (Hearn et al. 2011). Comparisons between plant species lists drawn up by different surveyors working in the same plots typically show agreement in the range of 50%–70% for a variety of habitats (Scott and Hallam 2002). Professionals working in the environmental and conservation sectors are therefore aware of the potential for inter-observer variation and its impact on data quality, but there is a dearth of information on the extent to which it is perceived to be an impediment to good decision-making in practice (Cherrill 2013a). If inter-observer variation causes few problems, then the issue may be largely irrelevant in day-to-day practice. However, if inter-observer variation in interpretation of habitat types is a cause of disagreement and poor decision-making there may be a mandate to change training and/or survey methods.\ud The focus of the present study is inter-observer variation in habitat mapping using two of the standard classifications in the United Kingdom, namely the Phase 1 habitat classification (JNCC 1993) and the NVC (Rodwell 2006). Studies focussing on these methods have revealed spatial agreement between surveyors using the same method at the same site in the range of 25%–70% (Cherrill 2013a). These studies, however, were conducted either as bespoke academic research projects designed to directly assess observer variation (Cherrill and McClean 1995, 1999a, 1999b, 2000, 2001; Hearn et al. 2011) or as part of Quality Assurance procedures within a large-scale national monitoring programme designed to detect landscape change (Stevens et al. 2004). The extent to which these results are representative of inter-observer variation in professional practice involving environmental assessment and site management planning is therefore unknown (Cherrill 2013a). None the less, it can be hypothesised that errors made in identifying vegetation types in these spheres of activity may be frequent and that there may be consequences for conservation assessments, site management and planning decisions.\ud The present paper uses a questionnaire survey of members of the Chartered Institute of Ecology and Environmental Management (CIEEM) in the United Kingdom to address two main questions. First, how frequently are errors in data detected in reports describing the results of vegetation surveys? Second, what are the practical consequences of these errors? CIEEM has approximately five thousand members in the UK. They are ideally placed to respond to these questions being employed primarily in environmental consultancy, planning authorities, governmental environmental agencies, and non-governmental conservation organisations. The Phase 1 and NVC survey methods are used only in the UK, but similar approaches are used elsewhere (Alexander and Millington 2000). The wider applicability of the study is, therefore, to illustrate the need to extend academic studies of inter-observer variation to investigate their relevance to the day-to-day experiences of environmental professionals. The implications for further research and development of professional practice are discussed

Federalism and Entrepreneurship: Explaining American and Canadian Innovation in Pollution Prevention and Regulatory Integration

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72611/1/j.1541-0072.1999.tb01969.x.pd

Incorporating concepts of inequality and inequity into health benefits analysis

BACKGROUND: Although environmental policy decisions are often based in part on both risk assessment information and environmental justice concerns, formalized approaches for addressing inequality or inequity when estimating the health benefits of pollution control have been lacking. Inequality indicators that fulfill basic axioms and agree with relevant definitions and concepts in health benefits analysis and environmental justice analysis can allow for quantitative examination of efficiency-equality tradeoffs in pollution control policies. METHODS: To develop appropriate inequality indicators for health benefits analysis, we provide relevant definitions from the fields of risk assessment and environmental justice and consider the implications. We evaluate axioms proposed in past studies of inequality indicators and develop additional axioms relevant to this context. We survey the literature on previous applications of inequality indicators and evaluate five candidate indicators in reference to our proposed axioms. We present an illustrative pollution control example to determine whether our selected indicators provide interpretable information. RESULTS AND CONCLUSIONS: We conclude that an inequality indicator for health benefits analysis should not decrease when risk is transferred from a low-risk to high-risk person, and that it should decrease when risk is transferred from a high-risk to low-risk person (Pigou-Dalton transfer principle), and that it should be able to have total inequality divided into its constituent parts (subgroup decomposability). We additionally propose that an ideal indicator should avoid value judgments about the relative importance of transfers at different percentiles of the risk distribution, incorporate health risk with evidence about differential susceptibility, include baseline distributions of risk, use appropriate geographic resolution and scope, and consider multiple competing policy alternatives. Given these criteria, we select the Atkinson index as the single indicator most appropriate for health benefits analysis, with other indicators useful for sensitivity analysis. Our illustrative pollution control example demonstrates how these indices can help a policy maker determine control strategies that are dominated from an efficiency and equality standpoint, those that are dominated for some but not all societal viewpoints on inequality averseness, and those that are on the optimal efficiency-equality frontier, allowing for more informed pollution control policies

Post-blast explosive residue : a review of formation and dispersion theories and experimental research

The presence of undetonated explosive residues following high order detonations is not uncommon, however the mechanism of their formation, or survival, is unknown. The existence of these residues impacts on various scenarios, for example their detection at a bomb scene allows for the identification of the explosive charge used, whilst their persistence during industrial explosions can affect the safety and environmental remediation efforts at these sites. This review article outlines the theoretical constructs regarding the formation of explosive residues during detonation and their subsequent dispersal and deposition in the surrounding media. This includes the chemical and physical aspects of detonation and how they could allow for undetonated particles to remain. The experimental and computational research conducted to date is discussed and compared to the theory in order to provide a holistic review of the phenomeno

Predicting environmental chemical factors associated with disease-related gene expression data

<p>Abstract</p> <p>Background</p> <p>Many common diseases arise from an interaction between environmental and genetic factors. Our knowledge regarding environment and gene interactions is growing, but frameworks to build an association between gene-environment interactions and disease using preexisting, publicly available data has been lacking. Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease.</p> <p>Methods</p> <p>We integrated publicly available disease-specific gene expression microarray data and curated chemical-gene interaction data to systematically predict environmental chemicals associated with disease. We derived chemical-gene signatures for 1,338 chemical/environmental chemicals from the Comparative Toxicogenomics Database (CTD). We associated these chemical-gene signatures with differentially expressed genes from datasets found in the Gene Expression Omnibus (GEO) through an enrichment test.</p> <p>Results</p> <p>We were able to verify our analytic method by accurately identifying chemicals applied to samples and cell lines. Furthermore, we were able to predict known and novel environmental associations with prostate, lung, and breast cancers, such as estradiol and bisphenol A.</p> <p>Conclusions</p> <p>We have developed a scalable and statistical method to identify possible environmental associations with disease using publicly available data and have validated some of the associations in the literature.</p