Odorous emission reduction from a waste landfill with an optimal protection system based on fuzzy logic

A critical review of decision support systems for brownfield redevelopment

Over the past two decades, many decision support systems (DSSs) have been developed to support decision makers and facilitate the planning and redevelopment process of brownfields. Existing systems are however often siloed in their approach and do not fully capture the complexity of brownfield sites from a sustainable development point of view. This critical review provides an insight into the development and implementation of DSSs, published and emerging, together with assessment of their strengths, limitations and opportunities for future integration. Brownfields DSS applications include: remediation technology selection; and land use planning; and risk assessment. The results of this review lead the authors to identify four opportunities to improve brownfield DSSs: (i) increased use of qualitative socioeconomic criteria, particularly costs and economic variables, (ii) decision-support during the early stages of brownfield redevelopment, (iii) the integration of predictive modelling methods, and (iv) improvements of user interfaces and modern web-based functionalities.

Analysis of Municipal Waste Development and Management in Self-Governing Regions of Slovakia

In the European Union, basic strategy results from the need to provide intelligent, sustainable, and inclusive growth, along with respect to social and economic impacts of waste treatment. The paper focuses on municipal waste and its separation. Generally, within global waste management initiatives, the main goal is to minimize the negative effects of waste on the environment, as well as to increase and optimize the sources’ efficiency in the waste economy. Research on municipal waste development and its separation was done in individual regions of Slovakia to find if socially weaker regions have worse waste treatment. The results were compared according to the waste development per inhabitant and per household, as well as through rate indexes, which are connected to relationships between waste, social, and economic indexes. The results confirmed research results from other countries that show that the volume of municipal waste is increasing due to increased living standards of inhabitants. However, on the other hand, waste separation rates also increased—mainly based on the legislative support.

Social Life-Cycle Assessment of Household Waste Management System in Kabul City

The present study constitutes the first social life cycle assessment (SLCA) study in Afghanistan and aims at assessing the social performance of the waste management system (WMS) of Kabul city. The system boundary considered includes households generating the waste, the sanitation department of Kabul city, scavengers, recycling shops, the recycling factory, and the local community living in its vicinity. Compared to previous SLCA studies that consider one stakeholder per organization, we distinguished between the manager and the worker level for each organization. In total, eight stakeholders, 90 inventory indicators, and 20 impact subcategories were investigated. Results show three main social issues: the overwork of scavengers, recycling shop owners and recycling factories’ workers and managers, the absence of communication and implication of the local community, and the poor cleanliness of the surroundings of the recycling factory and collection points. At the sanitation department, managers were found facing more psychological stress and overwork than workers, demonstrating the current isolation of the department inside Kabul’s local government. It seems nonetheless possible to improve Kabul’s WMS by redesigning the location of garbage bins and conducting communication campaigns towards consumers and the local community. That would help to minimize the nuisances associated with the handling of waste and to integrate better waste management activities into the socio-economy of Kabul city.

Prediction of odor complaints at a large composite reservoir in a highly urbanized area: A machine learning approach

Odorous compound emissions and odor complaints from the public are rising concerns for agricultural, industrial, and water resource recovery facilities (WRRFs) near urban areas. Many facilities are deploying sensors that measure malodorous compounds and other factors related to odor creation and dispersion. Focusing on the Metropolitan Water Reclamation District of Greater Chicago's (MWRDGCs) Thornton Composite Reservoir (7.9 billion gallon capacity), we used meteorological, operational, and H2S sensor data to train a 3-day advance-warning predictor of local odor complaints, so as to implement targeted odor prevention measures. Using a machine learning approach, we bypassed difficulties in modeling both physical dispersion and human perception of odors. Utilizing random forest algorithms with varied settings and input attributes, we find that a small network of H2S sensors, meteorological data, and operational data are able to predict odor complaints three days in advance with greater than 60% accuracy and less than 25% false-positive rates, exceeding MWRDGC's standards required for full-scale deployment. PRACTITIONER POINTS: A random forest algorithm trained on H₂ S, weather, and operations data successfully predicted odor complaints surrounding a large composite reservoir. Thirty-two data attribute combinations were tested. It was found that H₂ S sensor data alone are insufficient for predicting odor complaints. The best predictor was a Random Forest Classifier trained on weather, operational, and H₂ S readings from the reservoir corner locations. This study demonstrates odor complaint prediction capability utilizing a limited set of data sources and open-source machine learning techniques. Given a small network of H₂ S sensors and organized data management, WRRFs and similar facilities can conduct advance-warning odor complaint prediction.

Environmental Impact Assessment of Food Waste Management Using Two Composting Techniques

Food waste is a significant contributor to greenhouse gas emissions (GHG) and therefore global warming. As such, the management of food waste can play a fundamental role in the reduction of preventable emissions associated with food waste. In this study, life cycle assessment (LCA) has been used to evaluate and compare the environmental impact associated with two composting techniques for treating food waste using SimaPro software; windrow composting and the hybrid anaerobic digestion (AD) method. The study, based on a 1 tonne of food waste as a functional unit for a case study in the State of Qatar, concludes that anaerobic digestion combined composting presents a smaller environmental burden than windrow composting. The majority of the emissions generated are due to the use of fossil fuels during transportation, which correspond to approximately 60% of the total impact, followed by the impact of composting with 40% of the impact especially in terms of global warming potential. Environmental assessment impacts were the highest in windrow composting for the acidification impact category (9.39 × 10 − 1 kg SO2 eq). While for AD combined composting the impact was highest for the human toxicity impact category (3.47 × 10 kg 1,4 − DB eq).

Consumer’s Waste Classification Intention in China: An Extended Theory of Planned Behavior Model

Although there have been a variety of studies on waste classification management, there are few studies on how governments can effectively publicize waste classification knowledge in order to enhance citizen participation. Government publicity may be the key to the effective implementation of waste classification management in China. The purpose of this study is to examine the effects of government publicity, consumer attitudes, subjective norms, perceived behavioral control and consumer knowledge on consumers’ willingness to classify waste in the process of waste management in China. The methodology used for the study included data collected from a survey conducted among citizens from four cities in China, the extended theory of planned behavior model and a moderating effect analyses using the statistical software Amos17.0 and SPSS 22.0, utilizing structural equation modeling, hierarchical regression, and the interpretation of the results. The results show that government publicity has a significant positive impact on consumer attitudes, subjective norms, and perceived behavioral control. The positive effect of consumer attitudes and perceived behavioral control on waste classification intentions are significant. Consumer knowledge plays a significant role in moderating the effect of perceived behavioral control on waste classification intentions. The findings of this study are of great significance to government and public decision-making. The results strongly suggest that the government should vigorously publicize the knowledge of waste classification at the initial stage of implementation of waste classification. Furthermore, a detailed distinction between types of consumers and the role of personal values in the implementation of waste classification is considered as a direction of future research.

A Practical Approach to Reduce Greenhouse Gas Emissions from Open Dumps through Infrastructure Restructuring: A Case Study in Nanjing City, China

A new environmental ban has forced the restructure of open dumps in China since 1 July 2011. A technical process was established in this study that is feasible for the upgrade of open dumps through restructuring. The feasibility of restructuring and the benefit of greenhouse gas emission reductions were assessed according to field surveys of five landfills and four dumps in Nanjing. The results showed that the daily processing capacities of the existing landfills have been unable to meet the growth of municipal solid waste (MSW), making restructuring of the landfills imperative. According to an assessment of the technical process, only four sites in Nanjing were suitable for upgrading. Restructuring the Jiaozishan landfill effectively reduced the leachate generation rate by 5.84% under its scale when expanded by 60.7% in 2015. CO2 emissions were reduced by approximately 55,000–86,000 tons per year, in which biogas power generation replaced fossil fuels Fossil fuels accounted for the largest proportion, up to 45,000–60,000 tons. Photovoltaic power generation on the overlying land has not only reduced CO2 emissions to 26,000–30,000 tons per year but has also brought in continuing income from the sale of electricity. The funds are essential for developing countries such as China, which lack long-term financial support for landfill management after closure.