Industry,incidents and casualties in South West England: what is their relationship and are there social inequalities in their distribution?

This ecological study aimed, through the analysis of 1,146 wards in the South West of England (1998–2002), firstly, to examine whether chemical incidents and public casualties are more likely near complex industry (emissions to land, air or water: Integrated Pollution Control industry, IPC) or industry with emissions to air only (Local Air Pollution Control industry, LAPC). Secondly, the study examined whether industry, incidents and casualties are found close to deprivation. Social inequalities were examined across quintiles of wards. Fifty-two wards (4.5%) contained an IPC industry and 712 (62.1%) an LAPC. Incidents occurred in 132 wards (11.5%), with casualties in 59 (5.1%). Chemical incidents occurred more frequently in wards with LAPC (152, IPC 20); the same was true of casualties (211, 12). With each additional LAPC site in a ward, the risk of an incident rose by 22% (95% confidence interval [CI] 8–38%), suggesting a dose–response relationship. No clear social inequalities were found. In the South West of England, the public are more likely to be affected by an incident occurring at a simple LAPC site rather than a complex IPC site. This has implications for emergency planning which, at present, focusses most attention on the larger, more complex IPC sites.     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

Beyond the material grave: Life Cycle Impact Assessment of leaching from secondary materials in road and earth constructions

In industrialized countries, large amounts of mineral wastes are produced. They are re-used in various ways, particularly in road and earth constructions, substituting primary resources such as gravel. However, they may also contain pollutants, such as heavy metals, which may be leached to the groundwater. The toxic impacts of these emissions are so far often neglected within Life Cycle Assessments (LCA) of products or waste treatment services and thus, potentially large environmental impacts are currently missed. This study aims at closing this gap by assessing the ecotoxic impacts of heavy metal leaching from industrial mineral wastes in road and earth constructions. The flows of metals such as Sb, As, Pb, Cd, Cr, Cu, Mo, Ni, V and Zn originating from three typical constructions to the environment are quantified, their fate in the environment is assessed and potential ecotoxic effects evaluated. For our reference country, Germany, the industrial wastes that are applied as Granular Secondary Construction Material (GSCM) carry more than 45,000 t of diverse heavy metals per year. Depending on the material quality and construction type applied, up to 150 t of heavy metals may leach to the environment within the first 100 years after construction. Heavy metal retardation in subsoil can potentially reduce the fate to groundwater by up to 100%. One major challenge of integrating leaching from constructions into macro-scale LCA frameworks is the high variability in micro-scale technical and geographical factors, such as material qualities, construction types and soil types. In our work, we consider a broad range of parameter values in the modeling of leaching and fate. This allows distinguishing between the impacts of various road constructions, as well as sites with different soil properties. The findings of this study promote the quantitative consideration of environmental impacts of long-term leaching in Life Cycle Assessment, complementing site-specific risk assessment, for the design of waste management strategies, particularly in the construction sector.     

The green state and industrial decarbonisation

ABSTRACT

The large share of carbon emitted by energy-intensive industries in the extraction and processing of basic materials must be limited to decarbonise society and the economy. Ways in which the state can govern industrial decarbonisation and contributes to green state theory are explored by addressing a largely ignored issue: the green state’s industrial relations and its role in industrial governance. With insights from a Swedish case study, the tension between the state’s economic imperative and ecological concerns in greening industry are shown to persist. However, as the energy-intensive industry’s previously privileged position in the economy is weakening, industry is opened to decarbonisation strategies. While the case exposes a number of governance challenges, it also suggests potential areas where the state can pursue decarbonisation in energy-intensive industry and points the way to an active role of the green state in governing industrial decarbonisation and greening industry.     

Renewable energy consumption and its environmental impacts: A meta-regression analysis

This study involves a meta-analytical review of several articles, using the closest assumptions for the independent variable (renewable energy consumption), to determine the relationship with its environmental impacts. Furthermore, Sustainable Development Goal (SDG) in 2015 pays attention to related problems in both developing and developed countries. The effects of carbon emissions, natural resources, renewable energy consumption, and non-renewable energy on the environment are also reviewed. Following the separation of studies, the closest assumption was observed for the independent variable (energy source applications) of renewable energy. The meta-analysis was obtained using OpenMEE and JASP, and the results show the observed outcome, which was expressed in percentage. Based on the analysis, the Renewable Energy model has a value of 0.15, with the largest forest plots of 0.73, 0.69, and 0.80, recorded for studies 13, 19, and 23, respectively, while the least forest plots were recorded for studies 6, 11, 12, 15, 20, 22, 24, 25, 26, and 28. Therefore, renewable energy consumption, specifically in the mining industry, has the capacity to influence global warming. The respective industry has a unique influence on the processes that require renewable energy, for instance, the coal mining industry produces a smaller forest plot value, compared to oil and gas, or other mineral industries.     

Incorporating uncertainty in a chemical leaching assessment

Pesticide leaching models are being used to assist in the regulation and management of pesticides by indicating their potential for leaching to groundwater. Uncertainty in model input data is not, regrettably, included in most pesticide leaching assessments. In the work described here, we use logarithmic transformations of the attenuation factor (AF), a simple process-based index model, to represent uncertainty in a pesticide leaching assessment. Characterization of a wide range of pesticides as `leachers' or `non-leachers' for a specific Hawaii hydrogeological setting is facilitated by comparing the log-transformed AF, designated AFR, for each chemical with two reference chemicals for which leaching behavior in Hawaii is known. Defining a mean and uncertainty interval for the AFR index of each chemical being ranked provides a practical method of incorporating data uncertainty into a regulatory protocol.     

Domino effect in process-industry accidents - An inventory of past events and identification of some patterns

The paper presents an inventory, perhaps the most comprehensive till date, of the major process-industry accidents involving ‘domino effect’. The inventory includes, among other relevant information, the sequence of accidents that had occurred in each domino episode. The information has been analyzed to identify several patterns which may be useful in further work on understanding domino effect and reducing the probability of its occurrence in future. A concept of ‘local domino effect’ has been introduced.     

Carcinogen-Metabolizing Enzymes and Insecticides

Abstract

The present study was under taken to demonstrate the effect of some commonly used insecticides on the activity of cytochrome P450 system including cytochrome b5, aryl hydrocarbon [benzo(a)pyrene] hydroxylase (AHH), N-nirosodimethylamine N-demethylase I [NDMA-dI] and NADPH-cytochrome c reductase as phase I of drug oxidation. In addition, the activity of glutathione S-transferase (GST), glutathione reductase (GR), and the level of glutathione (GSH) were determined in the liver of male mice after oral administration of sumithion, dursban, chlordane, methoxychlor, heptachlor epoxide, and lindane as single (24 h) or as repeated doses for six consecutive days. Oral administration of sumithion, dursban, chlordane, methoxychlore, and heptachlor epoxide as repeated doses decreased: (i) the hepatic content of cytochrome P450 by 36, 37, 47, 37, and 67%, respectively, (ii) AHH activity by 28, 29, 70, 31, and 79%, respectively, (iii) NDMA-dI activity by 43, 44, 32, 27, and 31, respectively. On the other hand, sumithion, chlordane, and methoxychlore induced the activity of NADPH-cytochrome c reductase by 45, 62, and 43 respectively after repeated dose treatments. In addition, single and repeated-dose treatments of mice with lindane induced; (i) cytochrome P450 by 23 and 65%, respectively, (ii) cytochrome b5 by 49 and 131%, respectively, (iii) AHH activity by 64 and 50%, respectively. Repeated-dose treatments of mice with chlordane, methoxychlore, and heptachlor epoxide decreased the GSH level by 42, 38, and 68%, respectively and GST activity by 44, 44, and 55% respectively. Moreover, single- and repeated-dose treatments of mice with lindane decreased the GSH levels by 40 and 54%, respectively, and induced GST activity by 25 and 41%, respectively. Interestingly, single-dose treatments with chlordane, methoxychlore, and heptachlor epoxide decreased the activity of GR by 32, 38, and 31, respectively whereas repeated doses of these compounds induced such activity by 83, 50, and 64%, respectively. It is concluded that modifications in cytochrome P450 system by pesticides could potentiate the toxicity and carcinogenicity of environmental carcinogens such as polycyclic aromatic hydrocarbon and N-nirosodimethylamine (NDMA).     

化工园区综合风险评价中的公众参与研究

为确保公众与化工园区之间的和谐相处,分析化工园区综合风险评价中公众参与的现状,提出公众参与实施中所应遵循的原则、方法和形式,采用社会问卷调查的形式,验证了这一工作的必要性。阐述化工园区综合风险评价中公众参与应分为三个阶段,即早期公众参与、中期公众参与及持续公众参与,针对不同时期的具体情况,指出基本的工作程序。在公众参与调查中建立评价因素集的体系框架,并采用熵权法分析评价各因素的权重,结合公众＂幅值＂评分,综合得出公众对于化工园区建设、规划、准入项目及正常生产时带来影响的意见和建议的倾向性。首次提出在化工园区综合风险评价中增加公众参与这一内容,有利于增加政府机构办事的透明度,同时也确保公众的利益得到足够的重视。     

哈大齐工业走廊承接产业转移水环境风险评价

为了分析承接产业转移对水环境的影响,以哈大齐工业走廊为研究对象,在分析风险源、胁迫因子、生境、评价终点之间相互作用关系的基础上构建承接产业转移的水环境相对风险评价模型,并将研究区按照行政界线划分为3个风险评价单元,选取哈大齐地区重点承接的污染产业为风险源,选择水域作为风险受体,农田、林地、草地3种生境作为传播胁迫因子的媒介或载体,水质、水量、水生态为评价终点,对哈大齐承接产业转移水环境风险进行了定量评价.结果表明,哈尔滨市为最高风险区,其次是大庆市、齐齐哈尔市,相对风险分别为146.40、110.70和41.16.不同风险小区的最主要风险源不同,哈大齐3个城市主要风险源分别为医药制造业、化学原料与化学制品制造业及食品制造业.相反,各风险小区的主要胁迫因子大致相同,主要有需氧有机污染物、营养物质、生境破坏等.