Introduction To Environmental Impact Assessment

Glasson, John; Thérivel, Riki; Chadwick, Andrew

doi:10.4324/9780203023068

Cited by 264 publications

(233 citation statements)

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“…Sediments released into the water column from dredging and dredging-related activities can have a range of effects on nearby marine communities such as corals (Erftemeijer, Riegl, Hoeksema, & Todd, 2012;Jones, Bessell-Browne, Fisher, Klonowski, & Slivkoff, 2016), seagrasses (Erftemeijer & Lewis, 2006) and sponges (Bell et al, 2015). Standard approaches to environmental impact assessment (EIA; Glasson, Therivel, & Chadwick, 2013;Munn, 1979) and management typically use predictive modelling (EPA 2016; Gupta, Gupta, & Patil, 2005), which rely on a firm understanding of how ecosystems will respond to environmental disturbances and clarity in delineating benign and harmful conditions. Risk management strategies seek to balance the environmental benefits of strict regulation against the costs of alarmism.…”

Section: Introductionmentioning

confidence: 99%

Accounting for environmental uncertainty in the management of dredging impacts using probabilistic dose–response relationships and thresholds

Fisher

Walshe

Bessell-Browne

et al. 2017

Journal of Applied Ecology

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Dredging and related activities are common across nearshore marine environments, potentially threatening nearby ecosystems. Regulatory frameworks are essential for minimizing environmental impacts, yet rely heavily on a sound understanding of how ecosystems will respond to environmental stressors, and the thresholds that delineate benign and harmful conditions. Here, we use novel statistical approaches and mathematical tools to account for uncertainty in deriving in situ dose–response relationships and thresholds for the environmental management of dredging, based on estimates of the probability of non‐zero mortality of corals during a dredging campaign at Barrow Island, Western Australia. Using modified receiver operating characteristic curves, we derive thresholds with explicit Type I and Type II errors rates, across the full range of primary stress pathways and exposure dimensions (intensity, frequency and duration). Monitoring coral health and mortality can be expensive and water quality indicators are often used to supplement direct receptor monitoring during dredging management. We found strong relationships between coral mortality and a range of water quality exposure metrics, lending support to the use of water quality metrics as management tools for protecting corals during dredging. Metrics based on sediment deposition were more statistically powerful than those based on either light or turbidity, but may be more difficult to implement in practice. Thresholds reflecting aversion to a false sense of security in environmental protection or aversion to the costs of false alarms varied substantially for all exposure metrics examined. Synthesis and applications. Strategies for managing environmental harm under uncertainty are critical to achieving an informed risk‐weighted balance between environmental protection outcomes and development costs. Our study demonstrates the complexities of how communities respond to variable environmental exposure across a range of pressures in time and space, and the value of integrating probabilistic approaches in environmental management to account for that complexity and its associated uncertainty. Coral mortality was strongly related to a range of water quality exposure metrics associated with dredging activities, and regulatory thresholds based on water quality can provide a solid and cost‐effective foundation for protecting corals during dredging. The probabilistic dose–response relationships and thresholds presented here are the first to be derived from in situ data using dredging related coral mortality and represent a step forward in integrating formal decision science approaches into environmental management.

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Section: Introductionmentioning

confidence: 99%

Accounting for environmental uncertainty in the management of dredging impacts using probabilistic dose–response relationships and thresholds

Fisher

Walshe

Bessell-Browne

et al. 2017

Journal of Applied Ecology

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“…The example of Peru confirms the importance of linking budgets to environmental criteria and hosting external reviews to audit ecological performance (Jordan & Lenschow, 2010;Kivimaa & Mickwitz, 2006). Standardized EIAs in favorable actor constellations offer unused potential for increasing transparency, participation and acceptability of projects (Glasson, Therivel, & Chadwick, 2013). Moreover, policy tools such as Strategic Environment Assessment (SEA) recommended by the literature to enable a strategic, geographic implementation and the mitigation of environmental harm (Eggenberger & Partidário, 2000) are rarely applied.…”

Section: Results: Bpi In Peruvian National Sectorsmentioning

confidence: 99%

Mainstreaming across political sectors: Assessing biodiversity policy integration in Peru

Zinngrebe

2018

Env Pol Gov

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Mainstreaming biodiversity across political sectors and levels is a central challenge to conserving global biodiversity. This article introduces biodiversity policy integration (BPI) as an analytical approach for assessing the ecological performance of nonenvironmental sectors using the following criteria: inclusion, operationalization, coherence, capacity and weighting. To date, we know little about the barriers and enabling factors for integrating biodiversity into sector policies in resource intensive economies of the Global South. BPI in Peruvian political sectors of Agriculture and Irrigation, Economy and Finance, Energy and Mining, Production and Fishery, and Communication and Transport were analyzed based on sector strategies, related legal and strategic documents as well as qualitative expert interviews. While sectors commit to biodiversity conservation in general terms, a weak operationalization of biodiversity targets and low institutional capacity results in ineffective policy. Specific targets and indicators are not yet incorporated into sector strategies, national development planning, the evaluation of impact assessments or budget allocation. Biodiversity policies remain disconnected from the sectors' policy practices, which undermines the potential of reducing harmful incentives (Aichi target 3) and maintaining production within sustainable limits (Aichi target 4). Based on the results I identify the framing of sector-specific targets, favorable actor constellations and adaptive institutional learning arrangements as key elements for improving BPI. Facilitating agents, such as the environmental Ministry or intersectoral commissions, play a central role in generating ownership of biodiversity objectives in sector policy-making and supporting institutional learning processes.

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“…In addition, these factors are not dominant in a construction project. In a construction project, the work environment faced by workers is relatively complicated and varied, which is not well captured by the HRA method [29,30]. As a result, the probability of human error (HEP) cannot be accurately calculated in order to measure the influence of workplace environment on human error.…”

Section: Challenges Of Human Reliabilitymentioning

confidence: 99%

Estimating the Influence of Improper Workplace Environment on Human Error: Posterior Predictive Analysis

Liu

Shi

et al. 2018

Advances in Civil Engineering

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A model for identifying, analyzing, and quantifying the mechanisms for the influence of improper workplace environment on human error in elevator installation is proposed in this study. By combining a modification of a human error model with realworld inspection data collected by an elevator installation company, the influence paths of improper workplace environment on the conditional probability of human error were quantified using a Bayesian network parameter-learning estimation method and posterior predictive simulation. Under the condition of an improper workplace environment, the probability of human error increased by 80% of its original value, a factor much higher than that resulting from improper management. e most probable influence was found to be improper workmanship and changes in the information required by the worker, thus triggering cognitive failure and consequent unsafe actions by workers. e proposed methodology (posterior predictive simulation) provides a new approach in construction studies for quantifying the probabilistic levels of various causal paths, and the results show the key mechanism for the influence of improper workplace environment on human error using real-world mechanical installation data.

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Introduction To Environmental Impact Assessment

Cited by 264 publications

References 0 publications

Accounting for environmental uncertainty in the management of dredging impacts using probabilistic dose–response relationships and thresholds

Accounting for environmental uncertainty in the management of dredging impacts using probabilistic dose–response relationships and thresholds

Mainstreaming across political sectors: Assessing biodiversity policy integration in Peru

Estimating the Influence of Improper Workplace Environment on Human Error: Posterior Predictive Analysis

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