Responses of community to the possible use of recycled water for washing machines: A case study in Sydney, Australia

Recycled water is a valuable resource that has potential to free up potable water supplies and recharge systems while improving the environment. Recycled water for washing machine could be one of the options as new end use of recycled water to alleviate the demand on existing and limited water supplies. This paper summarizes the findings of a research survey in Sydney, Australia to explore the attitudes and opinions of community towards the use of recycled water for different purposes, especially for the washing machine. The survey showed that 97% of the respondents were aware of the persisting water shortage problem while more than 60% of the respondents supported the use of recycled water for washing clothes. This paper exposes the basic concern of participants for using recycled water in washing machine. Health issue was found as the most concerns of the community. The survey also presents the further conditions to be considered for using recycled water for washing machine according to the participants’ opinions. Correlation between knowledge and attitudes of respondents was also found in this survey.     

Using LCA to evaluate impacts and resources conservation potential of composting: A case study of the Asti District in Italy

Separate collection of municipal solid waste has overcome the 50% threshold in the Asti District in northern Italy, nearly one-third being composed of household and green organic waste. In order to address present and future solutions, it becomes therefore fundamental to assess the environmental performances of the current management of organic waste from separate collection. A from-gate-to-cradle life cycle assessment (LCA) model has been developed by expanding system boundaries, in order to carry out the assessment in the context of the whole waste management streamline. The environmental performances of an existing aerobic plant were made available, based on field measured data, by paying attention to the role and contribution of waste management subsystems. The need for actual and reliable data on materials and energy input, as well as gross and net gains from materials recovery, including benefits arising from use of compost in farming activities, was probably the major drawback that had to be faced. The study integrated the findings of different investigations from the literature with field measured data in order to obtain a more comprehensive framework representative of the area under study. The results may help public administrators to better understand the suitability of using LCA tools when dealing with solid waste management strategies.     

Environmental sustainability assessment in the process industry: A case study of waste-to-energy plants in Spain

This study proposes a technical procedure based on a life cycle approach for implementation of the environmental sustainability assessment (ESA) of several waste-to-energy (WtE) plants located in Spain. This methodology uses two main variables: the natural resources sustainability (NRS) and the environmental burdens sustainability (EBS). NRS includes the consumption of energy, materials, and water, whereas EBS considers five burdens to air, five burdens to water, and two burdens to land. To reduce the complexity of ESA, all variables were normalised and weighted using the threshold values proposed in the European Pollutant Release and Transfer Register regulation. The results showed the plants studied had a greater consumption of natural resources than Spain, ranging from 1.1 to 2.0 times higher than the Spanish reference consumption. The comparison of Spain with the BREF reference on waste incineration showed that only in the variable related to materials, did Spain have a lower consumption (1.80 times lower). In terms of EBS, air and land impacts were the highest contributors to global burden. The WtE plants presented higher burdens to air and water than Spain, whereas only one plant exceeded the average burden to land of Spain. Finally, this paper demonstrated the usefulness of the ESA methodology to reduce the complexity of LCA and assist the decision-making process in choosing the best option from an environmental point of view. This procedure can be used to obtain an overview of the environmental performance of WtE plants, as well as to assess individual burdens and thereby determine the main environmental hotspots, thereby improving the critical points of the process.     

Predicting the economic and demographic impacts of long distance commuting in the resources sector: A Surat basin case study

Predicting the economic and demographic impacts of resource development on regional areas is difficult to assess because of limited availability of analysis, difficulties of predicting where workforce are likely to be based, and different impacts on communities because of variations in size and economic structures. In this study modelling has been employed to identify future employment and demographic impacts of future resource developments on communities in the Surat Basin in southern Queensland, Australia. The analysis summarises potential employment increases over multiple projects and uses multipliers from Input–Output models to assess likely impacts by local government area when future workforce might commute to or live locally in the region. The results demonstrate that recent moves to commuting workforces limit the economic impacts on local and regional communities in complex ways.     

Perspectives on corporate social responsibility in the chemical sector: A comparative analysis of the Mexican and South African cases

In recent years, the debate on corporate responsibility has shifted from a focus on environmental management towards a broader concept of corporate social responsibility (CSR). This article examines the chemical industry's approach to CSR from the perspective of two emerging economies: Mexico and South Africa. The global chemical industry was one of the first to respond to public concerns about environmental pollution, toxic waste and human health by adopting an industry‐wide code of practice, known as Responsible Care. This article examines the extent to which the chemical industry has responded to the broader debate on CSR. On the basis of a comparative case study, this article argues that the response to social issues by Mexican and South African chemical companies has tended to be limited to the ‘community awareness and emergency response’ (CAER) or community dialogue component of the international voluntary management framework, Responsible Care. Similarities and differences in regulatory and institutional conditions, as well as different levels of civil society engagement, reveal additional limitations for CSR, beyond that of the Responsible Care framework. This article argues that the socio‐political context influences the extent to which companies embrace CSR, especially in emerging economies, and highlights several challenges for the chemical industry in moving forward on CSR: credibility, stakeholder engagement, value‐chain accountability, disclosure and transparency. Reflecting on these challenges, the authors conclude by recommending a renewed focus on: (1) developing a broader set of CSR management practices beyond Responsible Care; (2) institutionalizing stronger accountability measures, such as reporting and verification; and (3) developing multi‐stakeholder partnerships that complement regulation and build public sector regulatory and guidance capacity.     

Socioeconomic evaluation of the impact of natural resource stressors on human-use services in the Great Lakes environment: A Lake Michigan case study

The Great Lakes watershed is home to over 40 million people (Canadian and U.S.) who depend on a healthy Great Lakes ecosystem for economic, societal, and personal vitality. The challenge to policymakers and the public is to balance economic benefits with the need to conserve and replenish regional natural resources in a manner that ensures long term prosperity. Nine critical broad-spectrum stressors of ecological services are identified, which include pollution and contamination, agricultural erosion, non-native species, degraded recreational resources, loss of wetlands habitat, climate change, risk of clean water shortage, vanishing sand dunes, and population overcrowding. Many of these stressors overlap. For example, mining activities alone can create stress in at least five of these categories. The focus groups were conducted to examine the public’s awareness of, concern with, and willingness to expend resources on these stressors. This helped generate a grouping of stressors that the public is especially concerned about, those they care little about, and everything else in between. Stressors that the respondents have direct contact with tend to be the most important to them. This approach of using focus groups is a critical first step in helping natural resource managers such as Trustees and NGOs understand what subsequent steps to take and develop policy measures that are of most interest and value to the public. Skipping or glossing over this key first task could lead to difficulties with respect to survey design and model development in a non-market valuation study. The focus group results show that concern related to pollution and contamination is much higher than for any of the others. It is thus clear that outreach programs may be necessary to educate the public about the severity of some low-ranked stressors including climate change.     

Comparison of energy produced from waste by removing its different components: A case study of the waste landfill in Tehran

In developing and populated cities such as Tehran, a massive amount of municipal solid waste (MSW), both wet and dry, is transferred to landfills daily. Combustion is one of the most common methods of using mixed waste energy from the past to the present. The Dulong formula is widely used to calculate the energy released from MSW combustion. According to the constituent components of Tehran MSW, removing food waste leads to an increase in energy potential, which will be a suitable condition for energy production. In this work, the energy derived from the combustion of mixed and separated dry MSW generated in Tehran was calculated using the experimental Dulong formula and tables in Integrated Solid Waste Management (Tchobanoglous et al. 1993, McGraw‐Hill). The Dulong formula indicates that the use of Tehran mixed MSW (without separating materials for recycling) as a fuel source yields 8,966.40 KJ/kg while the use of Tchobanoglous et al. (1993) tables can generate 8,236 kJ/kg. By removing food waste and recyclable materials, the potential of energy production changes to 22,047 kJ/kg using the Dulong formula and 16,207 kJ/kg and the Tchobanoglous et al. (1993) tables. It indicates increase by 1.46 times and 46%, respectively. Regarding the 200‐ton capacity of the Tehran waste incinerator, the Dulong formula indicated generation of 4,409 MJ/day energy, and the Tchobanoglous et al. table presents 3,241 MJ/day. Therefore, considering that Tehran generates more than 4,000 tons of reject waste daily, it can easily be converted to energy rather than landfilled. This can alleviate the problem of buying land and construction of landfills and leachate generation.     

A critical review of the water quality classification system in Turkey: A case study on Meric Basin

An 11-year period of water quality data, collected by the Directorate of Sate Water Works of Turkey are thoroughly analyzed for the purpose of implementing water quality classes to water resources in the Meric Basin, located on the European land mass of Turkey. Water quality parameters are divided into four groups as physical, organic, inorganic, and bacteriological. The quality class of each group is evaluated by taking into account the poorest quality of any parameter in the group, after which a quality rank is assigned to the sampling station and the waterbody in question. This method of water quality classification imposed by the Turkish Water Quality Act, is then criticized with respect to a statistical approach.     

Local people's perceptions of participating in conservation in a heritage site: A case study of the Wuyishan Scenery District cultural and natural heritage site in Southeastern China

The perceptions and attitudes of local people in heritage sites strongly influence their behaviour related to protecting heritage resources and improving management. In this study, we collected pertinent data through a questionnaire and group discussions to examine local people's attitudes and perceptions toward participation in heritage protection in Wuyishan Scenery District (WSD). Logistic regression was used to identify the factors that influence local people's perceptions of heritage protection behaviours. The results indicate that education level is the most critical factor in local people's initiatives to protect heritage resources. Local people with higher education levels pay more attention to the status of WSD and behave more positively with regard to conservation. Gender and income are relatively important factors in perceptions of heritage. Males have better knowledge of heritage resources than females do, and inhabitants with higher income levels are more likely to participate in protection, especially after WSD was listed as a World Heritage Site. Education level was always a key demographic factor before and after WSD's listing on the Heritage List. Household size was a significant factor before WSD was listed on the Heritage List, but it was not significant after, when household income became a significant factor.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.