Tonle Sap Lake (TSL) in Cambodia and its many tributaries have a rich biodiversity. Many residents of the floating villages on TSL dispose of household wastes directly into the lake, which has resulted in large accumulations of plastic waste that seriously affect the quality of the watershed and its surrounding soils. It is therefore necessary to manage plastic waste more effectively, especially in rural regions in which there are no basic public waste collection services. The objective of the study was to capture the villagers’ perceptions of plastic waste. A perception survey was conducted using in-depth interview based on a standard questionnaire in the target area. The questions were designed to maximise the response rate and participant concentration. The collected data were analysed using statistical methods. The study captured the villagers’ perceptions of plastic waste, i.e. the reasons for using specific plastic items for consumption, avoidance of certain plastic items, plastic waste disposal methods and the willingness to participate in plastic waste separation and collection systems. Plastic bags accounted for most (27 %) of the plastic waste discharged into the lake or disposed of on land. Most respondents understood pollution problems were caused by discarding plastic waste directly into the lake. Of the 25 participants, 22 chose incentives (cash) as the most important factor that would motivate them to separate and collect plastic waste. Economic incentives have proven to be the most important factor for encouraging villagers on TLS to undertake waste separation and collection. The results of this study will assist in promoting plastic waste separation and collection in the floating villages of Cambodia.

Anthropogenic release of mercury, human exposure and environmental health are important and mercury management policies are required to effect significant change in Malaysia. To provide a useful information to facilitate the creation of strategic management policies for mercury as the Minamata Convention on Mercury is implemented in Malaysia, there is an urgent need to estimate the potential to reduce mercury release by applying different control measures, i.e. simple electrostatic precipitator and mercury-specific filter. Equally urgent is the need to clarify the alleviated environmental burdens from the reduced mercury releases by applying different control measures. Many researches have explored issues in terms of the mercury’ toxicity and the harm of mercury compounds worldwide. A lack of surveys to evaluate both on the reduction potentials and alleviated environmental burdens of mercury releases resulted in anthropogenic sources under different control measures has been observed. This study estimated the potential reduction and alleviation of the environmental burden of anthropogenic mercury released into the natural environment (air, water and land) in Malaysia under three emission control scenarios and identified the potential reductions. A life cycle impact assessment was applied to estimate an alleviated environmental impact under these scenarios. As a result, the environmental burden can be reduced by 77 % by applying the multipollutant emission control measures such as applying mercury-specific filter for coal combustion compared to no emission control measures. At this maximum, the harm to human health can be reduced by 3,730 disability-adjusted loss of life years and the harm to ecosystems can be reduced by 0.16 species/year. This study will assist decision makers to understand the magnitude of changes resulting from different emission control measures.

Cities are expected to play a major role in managing climate change in the coming decades. The actual environmental performance of urban centres is difficult to predict due to the complex interplay of technologies and infrastructure with social, economic, and political factors. Machine learning (ML) techniques can be used to detect patterns in high-level city data to determine factors that influence favourable climate performance. In this work, rough set-based ML (RSML) is used to identify such patterns in the Sustainable Cities Index (SCI), which ranks 100 of the world’s major urban centres based on three broad criteria that cover social, environmental, and economic dimensions. These main criteria are further broken down into 18 detailed criteria that are used to calculate the aggregate SCI scores of the listed cities. Two of the environmental criteria measure energy intensity and greenhouse gas (GHG) emissions. RSML is used to generate interpretable rule-based (if/then) models that predict energy utilisation and GHG emissions performance of cities based on the other criteria in the database. Attribute reduction techniques are used to identify a set of 7 non-redundant criteria for energy use and 9 non-redundant criteria for GHG emissions; 6 criteria are common to these two sets. Then, RSML is used to generate rule-based models. A 10-rule model is determined for energy intensity, while an 11-rule model is found for GHG emissions. Both models were reduced further by eliminating rules with weak generalisation capability. A key insight from the rule-based models is that social, environmental, and economic attributes are associated with energy intensity and GHG emissions due to indirect effects.

Regeneration is a widely implemented method in a thermal power plant for increasing the power plant efficiency. In a typical regenerative method, extracted steam from a steam turbine is mixed with cooling water in an open feed water heater to increase feed water temperature before feed water is heated, and becomes superheated steam. An alternative method of regeneration is possible for a biomass power plant that consumes the fuel with high moisture content. In this method, extracted steam is used to decrease the fuel moisture content before the fuel is combusted. The main objective of this paper is to compare both methods of regeneration. The reference power plant consists of a biomass boiler, a steam turbine, a condenser, and an open feed water heater. The boiler consumes 5.2 kg/s of fuel with a moisture content of 52 %, and generates superheated steam with a pressure of 4.5 MPa. Steam is extracted from the steam turbine at a pressure of 1.2 MPa, and supplied to the open feed water heater. The condenser pressure is 10 kPa. Turbine isentropic efficiency is 85 %, and pump isentropic efficiency is 70 %. The power output of the reference power plant is 10.0 MW. Two methods of increasing the power output are compared. In the first method, another open feed water heater is added to the reference power plant. The pressure of extracted steam supplied to this open feed water heater is 0.2 MPa. In the second method, a steam dryer is added to the reference power plant. The pressure of extracted steam supplied to the steam dryer is also 0.2 MPa. Simulation results indicate the first method increases the power output up to 3 %, whereas the second method increases the power output up to 7 %.

Waste-to-energy conversion such as anaerobic digestion has been widely promoted under the subsidies to decouple from fossil fuel dependence system and its inherent two-fold benefits. It could diversify the renewable energy matrix and divert the waste from the landfill. Co-digestion of two and more feedstocks could enhance bioenergy production and maximise waste recovery. However, the anticipated benefits are not absolute for all circumstances, varying across the type of co-substrate, pretreatment and other settings. The present study aims to overview the life cycle assessment (LCA) and the techno-economic assessment (TEA) of the anaerobic co-digestion processes. The results could provide an insight into the several critical parameters for sustainable co-digestion. Co-digestion of two or more feedstock is favourable since higher anaerobic digestion performances and higher profitability in TEA is shown. Cultivation of energy crops, transportation, pretreatment of feedstock and storage stage each contributes some shares to eutrophication potential (EP), acidification potential (AP), global warming potential (GWP), ozone depletion and fossil depletion. Generally, high anaerobic digestion performances and biogas upgrading can offset the negative environmental impact. Positive net present value is also observed from the co-digestion of feedstock.

A green and sustainable process is proposed for the synthesis of metal nanoparticles (NPs) by means of a solid disaggregation in a liquid phase. A solid metal substrate, embedded in a solution containing suitable capping agents and surfactants, undergoes comminution carried out by a rotating shaft of hardness greater than the one typical of the eroded substrate. The NPs have been characterized by dynamic light scattering for particle diameter. The effect of a technical solution replacing the presence of an abrading pad and the role of different physicochemical properties of the capping agent employed to damp particle aggregation have been investigated and discussed. In three out of four experiments carried out with different capping agents, the average metal NPs diameter is smaller than 10 nm. The present process does not require a complex experimental apparatus typical of dispersion machines customarily used on an industrial scale, generally relying upon direct or indirect milling equipment. With respect to the latter techniques, the advantages offered by the process proposed here stem from a possibility of monitoring the time trend of the NPs synthesis with minimal contamination of the as-produced NPs deriving from disaggregation of the milling medium.

Nowadays, increasing complexity of solved optimisation problems leads to necessity of dealing with computation time demand. In the case of network flow tasks, computation time is highly dependent on detail of transport infrastructure. The presented paper is concerned with developing novel approaches for transport infrastructure reduction using clustering analysis. According to the required outputs of the task, it is possible to variably change the detail of the network in individual territorial units to ensure the solvability of the task, but without significant distortion of the results. The main idea and novelty of the presented research is to have a finer construction only in the vicinity of the monitored subject. With a greater distance, it is possible to reduce the level of detail in the transport network. The principle of reduction technique is based on transformation of geographic coordinates with subsequent cluster analysis. K-means and hierarchical clustering are introduced and results of developed approach are shown on municipalities in Czech Republic. Consistency within clusters of both methods is evaluated using silhouettes. The presented methodology allows to solve optimisation of case studies more efficiently with greater detail in monitored region, which leads to more accurate solutions.

Multi-region input-output models have been used extensively for describing and analysing the production and trade of goods. However, there have been no prior publications on the use of such models to determine optimal trade benchmarks considering footprint limits. Such benchmarks can provide valuable insights for economic planning, in the same manner that pinch analysis targets provide insights in process integration. In this work, a mixed-integer linear programming input-output model is developed to minimize environmental footprint by adjusting production and trade levels in a cluster of regions or countries with specified final demand constraints. A case study based on a simplified, low-resolution model of the Philippines using land footprint as objective function is solved to illustrate this new approach.

Closed-loop processes are widely used in the chemical industry, for example in separation processes to recycle waste streams. However, the recycled streams represent a source of instability, especially when the overall system suffers a (desirable or undesirable) change in the operating conditions. In this case, the time required to reach a steady state is significantly longer, because of oscillations encountered in the leaving stream characteristics. The dimensions of such oscillations can reach high and even hazardous values, even if the new steady state is reached in a safe operating condition. This is why the knowledge of the dynamic closed-loop process behavior is essential to prevent hazardous situations. In this work, a general rate-based model of a closed-loop chemical absorption process is presented and the results of dynamic simulations are compared with published experimental data on absorption of carbon dioxide with aqueous monoethanolamine solution. The periphery is considered using dynamic models of the liquid distributors, the liquid holdup in the bottom of the columns as well as of the relevant heat exchangers and pipelines. Based on the simulations, the influence of different closed-loop process elements on the dynamic behavior of the overall configuration can be evaluated, enabling a cause-effect analysis of hazardous situations.

This study proposes a fractionation of proteins using solutions (5%) of Whey Protein Isolate (WPI) and supercritical carbon dioxide (scCO2) in a continuous reactor. The experiments were performed at different values of pressure, temperature, and residence times - 65.4, 34.3, and 32.3 min, respectively. a-lactalbumin (a-LA) and ß-lactoglobulin (ß-LG) levels were determined by HPLC. WPI used without treatment showed an a/ß ratio = 0.40. 16 MPa/55 °C and 16 MPa/60 °C were the conditions that suffered the most positive and negative influence of the increase and decrease in residence time, respectively. In the most severe condition, 24 MPa, 65 °C, and 4.0 mL·min-1, circular dichroism indicated that, despite not having obtained a high level of pureness, the fractionation technique employing scCO2 did not denature the proteins a-LA and ß-LG.