Abstract

Low-carbon (LC) cities are the cities that people long for today. LC environmental protection plays a very important role in people’s health. The construction of a city in LC is a great cause that contributes to the present and benefits the future. In this study, we propose a development and sustainability evaluation system for building low-carbon cities based on the Internet of Things (IoT). The study is novel in that it considers key areas such as urban planning, environmental issues and solutions, and how the Internet of Things can optimize low-carbon logistics and smart grids, with the aim of promoting the formation of low-carbon city models. This comprehensive approach not only presents problems and solutions in low-carbon urban planning but also focuses on how the Internet of Things can be used as a key technology to promote low-carbon urban development. The urban development of LC was constructed with a sustainable evaluation system, so that people could experience the life of LC. Through the investigation of the degree of atmospheric pollution of LC cities using the Internet of Things, this article found that the highest degree of atmospheric pollution was 30. The highest degree of atmospheric pollution in cities in LC without IoT was 53. The severity of water pollution in cities in LC using IoT technology ranged from 10 to 25, while those without IoT ranged from 30 to 60. The degree of soil pollution in LC cities using IoT technology was concentrated in 10–30, while those without using IoT were concentrated in 30–50. Through these experimental data, it could be seen that IoT technology could reduce environmental pollution, thus achieving the effect of LC cities. This shows that the use of IoT technology in LC cities was highly feasible.

Introduction

LC cities are currently a prominent topic of discussion and delight the imaginations of people around the world. The concept of LC cities, short for “Low-Carbon” cities, has gradually gained traction among the populace. People harbor a deep yearning for the LC lifestyle, envisioning medium-sized cities that are environmentally friendly and pristine, capable of fostering both health and happiness. Consequently, there is an ongoing surge in scholarly endeavors aimed at comprehensively understanding LC cities.

As public interest in LC cities continues to increase, so does the volume of research dedicated to unraveling their intricacies. Liu C, for instance, espoused the view that LC policies are not merely geared towards fostering economic development, but also towards mitigating the impacts of climate change. He posited that LC policies foster a symbiotic relationship between economic industrial structures and foreign investments, thus achieving mutually beneficial growth. Despite the promotion of regional innovation by LC policies, Liu cautioned that innovation might not produce immediate results [1]. Similarly, Xin L stated that the promotion of green and LC development has become a global consensus, but lamented the dearth of studies exploring the scientific nuances and repercussions of LC development [2]. Chen L, on the other hand, emphasized that the primary environmental challenge lies in carbon emissions arising from urbanization. He advocated for stringent measures to curb the growth of urban carbon emissions as part of experimental policies aimed at achieving carbon neutrality [3]. Colenbrander S shed light on the prevalent misconception that LC development is inherently more expensive than high-carbon development, a belief that often hampers opportunities for sustainable growth, especially in resource-constrained environments [4]. It is posited that integrating LC city construction with the Internet of Things (IoT) could potentially catalyze more comprehensive LC development, thereby fostering cities’ transformation towards greater sustainability.

Conclusions

With the increasing severity of pollution, people gradually began to pay attention to the development of LC, which can reduce environmental pollution and bring health to people. As a new technology, the IoT can play a very good role in the construction of LC cities. Cities become intelligent and can reduce many unnecessary pollutants, thus achieving the effect of reducing pollution. This paper studied the development of LC cities based on IoT, in hopes of improving the construction of LC cities through IoT technology. This paper tested the air pollution level, water pollution level, and soil pollution level of LC cities using the IoT technology and without the IoT technology. From the experimental data, it could be seen that the level of air pollution level, water pollution level, and soil pollution level after using IoT technology were lower than those without using IoT technology, which proved that the IoT technology was suitable for the LC development of cities and could reduce pollution. Due to the length of this paper, the experiments and discussions on LC cities were still insufficient and would be improved in the future. Finally, it was hoped that the LC of the city could develop better and better and that people could lead a life that was environmentally friendly and LC.

Abstract

Microplastics pose a severe threat to marine ecosystems; however, relevant mathematical modeling and analysis are lacking. This paper formulates two stoichiometric producer-grazer models to investigate the interactive effects of microplastics, nutrients, and light on population dynamics under different settings. One model incorporates optimal microplastic uptake and foraging behavior based on nutrient availability for natural settings, while the other model does not include foraging in laboratory settings. We establish the well-posedness of the models and examine their long-term behaviors. Our results reveal that in natural environments, producers and grazers exhibit higher sensitivity to microplastics, and the system may demonstrate bistability or tristability. Moreover, the influences of microplastics, nutrients, and light intensity are highly intertwined. The presence of microplastics amplifies the constraints on grazer growth related to food quality and quantity imposed by extreme light intensities, while elevated phosphorus input enhances the system’s resistance to intense light conditions. Furthermore, higher environmental microplastic levels do not always imply elevated microplastic body burdens in organisms, as organisms are also influenced by nutrients and light. We also find that grazers are more vulnerable to microplastics, compared to producers. If producers can utilize microplastics for growth, the system displays significantly greater resilience to microplastics.

Introduction

Plastic pollution has steadily increased due to widespread plastic use, insufficient disposal practices, and limited waste management capacity over decades. Plastic wastes discharged into terrestrial and aquatic habitats are considered a serious threat to biodiversity, due to their resistance to decomposition (Gall and Thompson, 2015, Carbery et al., 2018). The small plastic particles, ranging from 0.1 to 5 mm in size, are called microplastics (EFSA Panel on Contaminants in the Food Chain (CONTAM), 2016). Microplastics are observed almost in all aquatic habitats (Eerkes-Medrano et al., 2015, Peeken et al., 2018). Chronic exposure to microplastics presents several challenges for aquatic organisms (Cui et al., 2017, Duis and Coors, 2016, Nolte et al., 2017, Zhang et al., 2017, Khoironi et al., 2019, Sjollema et al., 2016, Besseling et al., 2014).

Studies have shown that microplastics can be absorbed, concentrated, and transported into various organisms, such as algae. This process significantly hampers algal growth, chlorophyll levels, and photosynthetic activity (Cao et al., 2022, Liu et al., 2019, Chae et al., 2019, Wu et al., 2021, Jiao et al., 2022, Gray and Weinstein, 2017, Zhang et al., 2017, Sjollema et al., 2016, Yang et al., 2020, Ferguson, 2011, Wang et al., 2020, Khoironi et al., 2019, Rodrigues et al., 2019, Salman et al., 2016). This inhibition may occur due to physical factors, such as the blockage of light and airflow (Bhattacharya et al., 2010, Wang et al., 2020, Salman et al., 2016, Bhattacharya et al., 2010), or interactions between microplastics and algae, including adsorption, aggregation (Zhang et al., 2017), and the destruction of algal cell walls through surface absorption (Liu et al., 2019). However, it is worth noting that some laboratory studies suggest that certain algae species may increase in the presence of smaller-sized microplastics, possibly because microplastic particles can be utilized as substrates for the growth of algae (Yokota et al., 2017, Mao et al., 2018, Jiao et al., 2022, Canniff and Hoang, 2018).

Discussion

Microplastics can be mistakenly ingested or adhere to the surfaces of marine organisms, resulting in significant adverse effects (Zhang et al., 2017, Liu et al., 2019, Sazli et al., 2023, Gregory, 1996, Derraik, 2002, Blarer and Burkhardt-Holm, 2016, Alomar et al., 2017). This paper presents two stoichiometric models to investigate population dynamics in the presence of microplastics in both field and laboratory settings. The interactive effects of light, nutrients, and microplastics on population dynamics have been rigorously studied.

For natural ecosystems, the OMUF model reveals complex dynamics. When the microplastic concentration is relatively low, the behavior of the system is strongly influenced by the initial conditions and can exhibit bistability or tristability. Conversely, when microplastics in the environment become excessively abundant, the only outcome is the extinction of grazers. Furthermore, the tolerance to microplastics of the producer-grazer system described in OMUF model (3.5) is significantly lower, compared to that of the system defined in NM model (2.11). This discrepancy potentially arises from the fact that in the natural ecosystem, grazers have to face more challenges and pay significant feeding costs, such as food scarcity, nutrient deficiencies, predation risk, multiple toxins, and human impact, making them more susceptible to microplastics.

Extreme light condition, either too low or too high, restricts the growth of grazers. When light intensity is excessively low, producers can only survive at low densities due to weakened photosynthesis, and grazers go extinct because of insufficient food. When light intensity is excessively high, the P:C ratio in producers becomes very low, and grazers go extinct due to nutrient deficiency. However, when light intensity falls within a moderate range, coexistence of both species may occur, and the system demonstrates a greater ability to withstand microplastics.

Abstract

This research is about how farmers adapt to water scarcity. Using experimental economics methods, field experiments were carried out in a region exposed to severe water scarcity in Colombia. Willingness of water users to cooperate in conforming to extraction caps, as a means of adapting to water availability declination was calculated. Two information treatment groups were implemented in order to assess water allocation decisions when: (i) the amount of water was reduced and (ii) time before aquifer exhaustion was announced. Extant literature on cooperation in common-pool resources (CPR) has focused on demonstrating to what extent resource users depart from egoistic attitudes. Alternatively, the sustainability of water resources requires more research to further understand cooperative behavior. Since the literature on water scarcity is classified in three orders, namely physical, institutional, and socio-political, behavioral dimensions are suggested as a subdivision of the social order. This, in turn, may help to operationalize strategies aimed at improving adaptation to all orders of scarcity. The quantitative results suggest that farmers are inclined to follow the cap. The main difference between the quantity and time treatments differs in that in the time treatments farmers allocate much more water to be consumed in the future, whereas in the former, they prefer to allocate more water to be consumed in the present. Adaptation options provide favorable inputs for implementing the Sustainable Development Goals, especially SDG 6, which is related to water use efficiency. Target 6.4 establishes that, by 2030, water efficiency and extraction sustainability should be accomplished. Thus, water policy interventions might benefit from this contribution. However, since success in water conservation programs might be difficult to achieve due to complexity in human-decision making, more research is needed to deepen our understanding of cooperation drivers in aquifer conservation.

Introduction

Despite the abundance and precision of current information on aquifers status ( van der Gun, 2022 ), this type of data – commonly managed by governmental institutions – rarely flows to the communities that depend upon them ( Margat & van der Gun, 2013 ). In effect, underground water availability data is currently assessed through satellite and underground monitoring of aquifer levels, but farmers´ communities do not have access to this information in a format they can readily use. Climate change is entering the aquifer overexploitation game as a new player ( Damania et al., 2017 ), since droughts are becoming more frequent than in the past ( UNWATER, 2023; Yuan et al., 2023 ); therefore, public environmental and water entities promote water conservation during droughts. Public entities usually stimulate the reduction of water extraction volumes by instructing users to consume less or save the resource. This information, however, lacks the necessary context and specificity, two features that play an important role in water extraction curbing adapted to ensuing water scarcity.

Although water scarcity has an important political dimension ( Metha, 2007 ), from the perspective of its physical and social dimensions, it can be observed how climate change is motivating farmers towards strategies to face the challenge. In spite of the complexity of hydrogeological information, farmers certainly want to know more about the status of the aquifers they are exploiting. They need information not only about the effects of their extraction decisions, but also about the way to moderate these decisions as an adaptation to scarcity according to aquifers’ statuses.

Conclusions

This article was designed for presenting the results on how farmers adapt to water scarcity. Framed field experiments were run to collect quantitative data on the decisions made by farmers when they were exposed to reductions in water availability. Time and water quantity treatment groups were prepared to test their effects on water allocation as limited by suggested extraction caps. Quantitative and qualitative analysis of data and information were carried out. Behavioral regularities and social institutions were drawn from the quantitative data and graphics and the narratives expressed by the players after the experiments.

The setting for the understanding of adaptation strategies was demarcated by the limits imposed by nature. For this reason, water availability as a physical limiting factor for water extraction was used as an instrument to connect allocation, decision-making and intertemporal consequences for adaptation. Thus, limited availability under time and quantity limits pushed the farmers (players) to decide whether to cooperate or not in water conservation. Thus, the individuals who cooperated better were adapting to water scarcity. More precisely, the farmers informed on time before aquifer exhaustion, revealed greater awareness about the possibilities of cooperation. Contrarily, in the control group situation, farmers allocated much more water to all uses and the cap volume was reached in most of the rounds. While in the time and quantity treatment groups, the aggregated water volumes declined through the time (rounds), in the control group this amount averaged 1800 m3 (close to the cap). It can be said that the communication amongst farmers on how to manage remaining stocks, and, similarly the hydrogeological information play a key role in incentivizing the cooperative behavior under extraction caps contexts. Since the stability of cooperation was part of the research aims, providing quantitative information to farmers on extraction decisions and the remaining time of aquifer availability is suggested as a key factor to more effectively address the adaptation to water scarcity.

Abstract

Significant population growth with rapid economic development have led to water scarcity problems around the world. Currently, most of the simple water scarcity assessment methods only refer to per capita water use, failing to take into account actual water availability and actual human domestic water use. Therefore, we have developed a simple and practical method to assess water scarcity, incorporating total water resources, water use efficiency, and the proportion of domestic water. In this approach, a new water scarcity index is employed to describe different levels of water scarcity using various thresholds based on the basic daily human water use per person. This may help to visualize the extent of water scarcity in a region while focusing on human interests. To illustrate this approach, we take China–the world’s largest developing country–as an example, analysing its nationwide water scarcity in 2021 while validating it with the results of other scholars on China’s water scarcity. The results show that our water scarcity assessment index is very accurate, revealing that in 2021, the disparity in water resources between the northern and southern regions of China remains substantial, with severe water scarcity still widely concentrated in northern China.

Introduction

Continuous water supply plays a vital role in daily life and social development ( Ethaib et al., 2022 ). However, increasing water consumption is due to the significant population growth and rapid economic development, resulting in extremely high water resource pressures, which cause water scarcity in numerous places around the world ( Liu et al., 2017 ). For instance, in regions such as Greater London with high population density, intense irrigation present in areas like the High Plains of the United States, and nations like India that exhibit both traits, there is a prevalent issue of water scarcity ( Mekonnen and Hoekstra, 2016 ). Nevertheless, in addition to direct water supply shortages caused by the forces of nature, human factors, as well as socio-political factors, are often overlooked, leading to the masking of the causes of scarcity. This complexity of water scarcity is labelled by Mehta as ‘real’ scarcity (related to socially and ecologically relevant physical phenomena like grass cover, fodder, distance to water for disadvantaged groups, cycles of natural resource abundance and scarcity, agro-meteorological hydrology, etc.) and ‘manufactured’ scarcity (constructing water scarcity as a perpetual and pervasive natural phenomenon, the industry of disaster relief and drought relief, and perverse benefits) ( Mehta, 2003 ). Moreover, there are also sudden and uncontrolled factors affecting water resources, such as the outbreak of the COVID-19 pandemic crisis, which has put many additional pressures on water resources, including the increase in local agricultural irrigation brought about by the localised production of food, and the parallel alteration of the virtual water trade caused by the changes that have taken place in the food trade ( Al-Saidi and Hussein, 2021 ).

Results

3.1. Statistical analysis of the results

A comparison of the water scarcity index calculated using Eq. (1) for each region of China, with a threshold of 0.2 (no stress), is shown in Fig. 2 . The results show that most regions in China are still suffering from water problems, including some economically developed cities with heavy water problems, such as Beijing (0.01), Tianjin (0.008), and Shanghai (0.02). In contrast, Qinghai (1.43) and Xizang (10.56) have abundant water resources, which are significantly higher than in other regions.

3.2. Spatial analysis of the results

In this study, ArcGIS Pro software was used to raster water resource data from various provinces in China in order to comprehensively and visually assess water scarcity across the country. As can be seen in Fig. 3 , the water scarcity index shows obvious spatial distribution differences, mainly between the northern and southern regions of China. Overall, the water scarcity index shows absolute scarcity in the north and no stress in the south. Specifically, a wide range of areas in northern China, including Inner Mongolia, Liaoning, and Shaanxi, exhibit water scarcity and some pressure on water resources. It is worth noting that some areas in the north also show absolute water scarcity, especially in Beijing, Tianjin, Hebei and Shanxi, indicating that the available water resources in these regions do not meet the minimum basic human needs of the region.

Abstract

Previous research has explored the impact of telework on homes and offices separately, but it is necessary to examine these domains together, as energy savings in one may be offset by increased consumption in the other. Therefore, the present study aims to fill this gap by quantifying the impact of telework on the energy use of homes and offices simultaneously. Using a medium office building reference model and four home models, the present study simulates telework scenarios from 0 % teleworking to 100 % teleworking in 20 % increments in six different Canadian climate zones in EnergyPlus. The results show homes and offices with technologies that adapt to occupancy levels (adaptable) consume less energy and produce less emissions compared to inadaptable ones. However, energy use associated with homes increases slightly due to longer hours of occupancy. Emissions associated with telework depend on the impact of telework on internal heat gains, climate zones, and sources of energy (emission factors). The results demonstrate that the increase in energy consumption associated with various teleworking scenarios ranges from approximately 0.6 %–6.1 %. Similarly, the increase in emissions varies, ranging from nearly 0.5 % to 7.6 %. The present study is the first comprehensive study that considers the home type and size and other statistical data for different Canadian climate zones. The results have major implications for employers and policymakers aiming to adopt telework as a sustainable practice. The results of this study create the foundation for future comprehensive studies on teleworker behavior, transportation, and the internet use associated with telework.

Introduction

1.1. Teleworking and occupancy
Partial occupancy in offices has become a more common global phenomenon after the COVID-19 pandemic, as many employers started offering flexible schedules with telework options [[1], [2], [3], [4]]. Teleworking has different definitions but it can be generally defined as an umbrella term referring to working outside of a traditional office by using the internet [5]. Telework is often considered a sustainable alternative to traditional work arrangements as it can potentially reduce commute or the need for office space [4]. However, recent studies have shown that the potential sustainable benefits of teleworking significantly rely on teleworkers’ behaviors and decisions for four domains of homes, offices, transportation, and the internet [4,6,7]. Among all the four domains, the relationship between homes and offices has been less studied – especially quantitatively. Thus, the literature is inconclusive about the impact of telework on homes and offices concurrently.

Offices and homes are not typically designed to adapt to partial occupancy, meaning building systems such as HVAC systems are designed for full capacity. For instance, actual occupancy pre-COVID was usually between 50 % and 70 % in office buildings while office buildings are assumed to be operating under near-full occupancy [8,9]. Consequently, studies have shown building systems normally operate at their full capacity without considering occupancy [10,11]. The disproportionate decreases in the energy use of office buildings compared to occupancy during the COVID-19 pandemic are evidence of this phenomenon [[12], [13], [14], [15], [16], [17]]. Meanwhile, home energy use may increase significantly as a result of the use of more comfortable temperature setpoints or even the purchase of new HVAC equipment, like air conditioning. In part-time teleworking scenarios, such equipment may be operated every day, regardless of occupancy [6,18,19]. Therefore, it is important to have buildings that can adapt to partial occupancy [20]. As a result, there is an urgent need to quantify the impact of telework and partial occupancy on two main building types, homes and offices, under different teleworking scenarios.

Results

In this section, energy use and emissions associated with offices, homes, and their integrated net are described in Sections 3.1 Offices, 3.2 Homes, 3.3 Combined emissions of homes and offices. The results presented in the Offices and Homes sections are applicable to their respective domains.

3.1. Offices
3.1.1. Internal gains and inadaptable and adaptable offices
Fig. 12 shows the internal heat gain in W for adaptable and inadaptable offices in six different climate zones. While previous studies pointed to the impact of internal gains [22], the present study quantifies the impact. Fig. 12 shows reduced heat gains from people, equipment, lights, hot water equipment, gas equipment, and other equipment. The reduction in heat gains causes more demand for heating in buildings.

Abstract

Recycling of abandoned waste bottom ash has been a key issue in Republic of Korea in terms of environmental protection as well as economic concern. In this work, a method for recycling of abandoned bottom ash has been discussed based on the results from laboratory and industrial-scale experiments. Abandoned bottom ash was magnetically separated and properties of magnetically separated bottom ash samples as well as properties of mortar and masonry cement brick made of bottom ash were investigated. According to the experimental results, bulk and skeletal densities were ranked in the order of strongly magnetic > weakly magnetic > as-received > non-magnetic (from heavier to lighter) bottom ash. From laboratory-scale experiments, compressive strengths of mortars made of bottom ash samples (measured by ASTM C 109) were lower than that of mortar made of standard sand. Among bottom ash samples, mortar made of non-magnetic bottom ash (after removal of unburnt carbon) showed higher compressive strength with lower thermal conductivity (measured by ASTM C 1113) and weight than others. Masonry cement brick made of magnetic bottom ash showed lower weight and thermal conductivity than those made of standard sand, while meeting the KS strength guideline as a masonry cement brick. The results suggest the applicability of bottom ash as lightweight aggregate for production of masonry cement brick. However, considering the lower strength obtained from masonry cement brick made of as-received bottom ash (without removal of unburnt carbon), unburnt carbon content should be removed prior to its utilization as lightweight aggregate.

Introduction

Consumption of fossil fuels for operation of coal fired power plant has been consistently increasing all over the world (International Energy Agency, 2009; Korre et al., 2010; Leblond, 2006; Shafiee & Topal, 2008). Although reduction in CO2 emission is very critical issue in this industry (Hussain et al., 2022), recycling of waste by-products is as important issue as the reduction of CO2 emission in terms of environmental protection (Abbas et al., 2020; Bui et al., 2019; Lee et al., 2020; Meek et al., 2021; Oakes et al., 2019) considering the amount of waste that has been generated so far. Approximately 730 million tons of bottom ash (Abbas et al., 2020) and 600 million tons of fly ash (Çiçek & Çinçin, 2015; Nyale et al., 2013) are annually produced in the world. Although fly ash has been successfully utilized as a supplementary cementitious material due to its beneficial properties such as reduction in the heat of hydration (Atiş, 2002a, 2002b; Langan et al., 2002; Matos et al., 2020; Nocuń-Wczelik, 2001; Schindler & Folliard, 2005), improvement in workability (Atiş, 2002b; Leung et al., 2016; Nocuń-Wczelik, 2001; Uysal et al., 2012; Yao et al., 2015), and long-term strength and durability (Pala et al., 2007; Siddique, 2003; Tikalsky et al., 1988), most of the bottom ash has not been recycled and abandoned in the waste storage site.

The utilization of bottom ash as a supplementary cementitious material has been limited. The chemical compositions of bottom ash are similar to that of fly ash. However, the particle size is larger and the structure is more crystalline than fly ash. For this reason, the pozzolanic activity of bottom ash is very weak. The work of (Cheriaf et al., 1999) showed that bottom ash did not react with calcium hydroxide at early ages. The pozzolanic activity was very slow until 28 days, and became accelerated after 90 days. Jurič et al. (Jurič et al., 2006) recommended to replace up to 15 wt% of cement by bottom ash to use it as a supplementary cementitious material. Kula et al. (Kula et al., 2002) showed that bottom ash can be used as a supplementary cementitious material depending on its particle size distribution. Jaturapitakkul et al. (Jaturapitakkul & Cheerarot, 2003) observed a glassy aluminosilicate phase (diffused halo maxima) at 20–27° 2θ (Cheriaf et al., 1999; Chindaprasirt et al., 2009) that can be a source of pozzolanic reaction, but reported that the pozzolanic activity of bottom ash can be increased by grinding the particle size lower than 45 μm. According to the literature, pozzolanic activity of bottom ash was so slow or weak that it cannot be effectively utilized as a supplementary cementitious material without additional mechanical or chemical treatment (Filipponi et al., 2003; Liu et al., 2018; Mangi et al., 2018).

Conclusion

In this work, magnetic separation was applied on bottom ash that was stored in the pond site of Hadong coal fired power plant. Properties of magnetically separated bottom ash were analyzed, mortar specimens as well as masonry cement brick samples were prepared, and compressive strength, water absorption, and thermal conductivity were measured. According to the results obtained from this work, following conclusions can be drawn.

1) Magnetic separation with 1000 and 3000 gauss magnet was effective for separating bottom ash samples that contains higher amount of magnetite. As a result, bulk and skeletal density of strongly magnetic bottom ash were higher than those of as-received bottom ash. Non-magnetic bottom ash showed the lowest bulk and skeletal density.

2) Pozzolanic activity of bottom ash was ranged 53 ~ 62% of fly ash that was stored at the same pond site. Considering the particle agglomeration observed from the fly ash, it is possible to evaluate the pozzolanic activity of bottom ash either as non-pozzolanic or as very weakly pozzolanic.

3) From laboratory scale experiments, non-magnetic bottom ash showed the better performance than strongly magnetic bottom ash in terms of compressive strength and thermal conductivity. Since large amount of unburnt carbon stayed together with non-magnetic bottom ash, removal of unburnt carbon is a key factor for successful utilization of non-magnetic bottom ash.

4) Masonry cement brick made of magnetic bottom ash showed 40% reduction in unit weight, 20% reduction in thermal conductivity. Utilization of non-magnetic bottom ash for masonry cement brick production after removal of unburnt carbon can also be a successful application, considering the results from laboratory-scale experiments (density and thermal conductivity was lower for non-magnetic bottom ash).

Abstract

Introduction

Material and methods

Results and discussion

Conclusions

Acknowledgments

Supplementary materials

Reference

Abstract

     Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep learning model, iDeepAir, to predict surface-level PM2.5 concentration in Shanghai megacity and link with MEIC emission inventory creatively to decipher urban traffic impacts on air quality. Our model exhibits high-fidelity in reproducing pollutant concentrations and reduces the MAE from 25.355 μg/m3 to 12.283 μg/m3 compared with other models. And identifies the ranking of major factors, local meteorological conditions have become a nonnegligible factor. Layer-wise relevance propagation (LRP) is used here to enhance the interpretability of the model and we visualize and analyze the reasons for the different correlation between traffic density and PM2.5 concentration in various regions of Shanghai. Meanwhile, As the strict and effective industrial emission reduction measurements implementing in China, the contribution of urban traffic to PM2.5 formation calculated by combining MEIC emission inventory and LRP is gradually increasing from 18.03% in 2011 to 24.37% in 2017 in Shanghai, and the impact of traffic emissions would be ever-prominent in 2030 according to our prediction.

Introduction

     Air pollution is a large obstacle to the world’s future sustainable developments, and millions of people die from air pollution-related diseases every year around the world (Zheng et al., 2017). This is seriously severe in some developing countries like China (Lelieveld et al., 2015), which has the highest country-level values globally for the population-weighted annual average concentration of PM2.5 (Tichenor and Sridhar, 2019; Zhang et al., 2012) and has been a major public health concern in recent years (Li et al., 2019a) . Shanghai, one of the most developed and populous cities in China, has suffered severe increasing haze episodes mostly attributed to the severe particle pollution especially fine particles (particles ≤2.5μm in aerodynamic diameter; PM2.5)(Han et al., 2020) since 1990s with the rapid urbanization and industrialization (Wang et al., 2015) . Under these circumstances, air pollution-related diseases have emerged gradually, such as respiratory diseases in the elderly and preterm birth and low birth weight for birth when maternal exposure to PM2.5 in Shanghai(Li et al., 2019a; Liu et al., 2017) .

Conclusions

     In this article, we propose a novel method to quantify the influence of anthropogenic emissions on PM2.5 concentration with a novel and traceable deep learning model. Our experiment results indicate that the proposed model could achieve better fitting and prediction performances than the LSTM, GBRT, Seq2Seq, DA-RNN model and other deep learning models. Furthermore, we output the contributions of input parameter to the prediction in LRP method and visualize and analyze the spatial correlation between traffic flow and PM2.5.

     In addition, we discover that transportation emissions will play the most dominate role in future urban air pollution, and how to reduce traffic emissions are an unavoidable issue on achieving sustainable developments in modern cities. Meanwhile, to some extent, new energy vehicles can be considered as an effective way to reduce traffic emissions. However, the current promotion policies and efforts are far from enough. To further improve urban air quality, we need some more effective and powerful measurements in response to the rapid growth of urban traffic emissions.

Abstract

     Globally, to ensure food security bio-based fertilizers must replace a percentage of chemical fertilizers. Such replacement must be deemed sustainable from agronomic and greenhouse gas (GHG) emission perspectives. For agronomic performance several controlled protocols are in place but not for testing GHG emissions. Herein, a pre-screening tool is presented to examine GHG emissions from bio-waste as fertilizers. The various treatments examined are as follows: soil with added mineral nitrogen (N, 140 kg N ha−1) fertilizer (MF), the same amount of MF combined with dairy processing sludge (DS), sludge-derived biochar produced at 450 °C (BC450) and 700 °C (BC700) and untreated control (CK). These treatments were combined with Danish (sandy loam) or Irish (clay loam) soils, with carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions and soil inorganic-N contents measured on selected days. During the incubation, biochar mitigated N2O emissions by regulating denitrification. BC450 reduced N2O emissions from Danish soil by 95.5% and BC700 by 97.7% compared to emissions with the sludge application, and for Irish soil, the N2O reductions were 93.6% and 32.3%, respectively. For both soils, biochar reduced CO2 emissions by 50% as compared to the sludge. The lower N2O reduction potential of BC700 for Irish soil could be due to the high soil organic carbon and clay content and pyrolysis temperature. For the same reasons emissions of N2O and CO2 from Irish soil were significantly higher than from Danish soil. The temporal variation in N2O emissions was correlated with soil inorganic-N contents. The CH4 emissions across treatments were not significantly different. This study developed a simple and cost-effective pre-screening method to evaluate the GHG emission potential of new bio-waste before its field application and guide the development of national emission inventories, towards achieving the goals of circular economy and the European Green Deal.

Introduction

     Agricultural sources of greenhouse gas (GHG) emissions crucially influence climate change. During the period from 2007 to 2016, GHG emissions from agriculture, forestry and land use contributed about 23% of total net anthropogenic emissions, and emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from agriculture accounted for 13%, 44% and 81% of the anthropogenic emissions, respectively (IPCC et al., 2019). In November 2016 the legally binding international treaty on climate change called the Paris Agreement was adopted by 195 Parties. The key messages of the Paris Agreement include 1) limiting global warming to well below 2 °C, preferably to 1.5 °C, compared to pre-industrial levels; 2) establishing climate resilience and mitigating GHG emissions without threatening food production; and 3) aligning financial flows with pathways for low GHG emissions and climate-resilient development (UNFCCC, 2015). Therefore, the reduction of GHG emissions from agricultural soils with new effective mitigation strategies within the framework of the Paris Agreement becomes vital for the achievement of global warming reduction goals.

Conclusions

     Addition of biochar from pyrolysis of dairy sludge (DS) to soils together with mineral N fertilizer instead of directly adding DS, substantially reduced emissions of N2O to a level near that of untreated soil. Biochar pyrolyzed at 450 °C (BC450) reduced emissions of N2O by 95.5% and CO2 by 59.4% when applied to a Danish sandy loam soil (DA), and from an Irish clay loam soil (IR), emissions were reduced by 93.6% and 57.1%, respectively. Biochar from 700 °C pyrolysis (BC700) suppressed 97.7% and 49.7% of N2O and CO2 emissions from DA soil, and 32.3% and 62.4% from IR soil. Biochar shows no effect on CH4 emissions. Pyrolysis conditions and soil properties significantly affect the suppression of N2O emissions by biochar. This study provides a simple and cost-effective tool to examine the GHG emission potential of bio-waste before applying it in agricultural lands and helps in developing national emission inventories.

Abstract

     This work suggests an optimal strategy to sort and recycle plastic waste as a renewable energy resource with maximizing economic feasibility and mitigating environmental pollution. To derive the optimal sorting and recycling strategies of plastic waste, a novel optimization model is developed; it calculates the overall profit by subtracting the profit of recycling plastic from the total annualized cost. Then the model is used to identify the optimal strategy to sort and recycle plastic waste as a renewable energy resource in mixed-integer nonlinear programming that maximizes the overall profit. In the derived optimal sorting and recycling strategy, high-density polyethylene is recycled to produce downgrade plastic; low-density polyethylene, polypropylene, and polystyrene are recycled as pyrolysis oil; and polyethylene terephthalate is recycled to produce refuse plastic fuel. The derived optimal case can significantly increase the overall profit by about 3,137% (i.e., 35 US$/1 kg of recycled plastic), and 492% (i.e., 29 US$/1 kg of recycled plastic) compared to conventional case in South Korea and Japan respectively.

Introduction

     The demand for plastics has rapidly increased in many industries because of their versatility, and easy production. Consequently, plastic waste is discharged in massive quantities; estimates of plastic waste discharged into rivers, lakes, and seas is 9–23 million t per year globally (Borrelle et al., 2020; Masuda et al., 2001). Thus, the importance of plastic waste recycling is increasing (Shah et al., 2015; Zhang et al., 2020). Plastic waste is a mixture of different types, so it must be sorted into before it is recycled (Gundupalli et al., 2017; Hearn and Ballard, 2005; Lim and Cho, 2003). Economically-viable sorting and recycling of plastic will yield a cheap and abundant source of valuable chemicals and renewable energy (Gadaleta et al., 2020). However, current systems to sort and recycle plastic waste are not optimized, so their costs are high. Thus, only 27.2 wt% of plastic waste is recycled, whereas 36.4 wt% is landfilled, and 36.4 wt% is incinerated (Vieira et al., 2022). Therefore, the soil and air pollution according to the landfilled plastic and the significant amount of SOx, NOx, and CO2 emitted in the incineration of waste plastic is serious. The types of recycled plastic have different uses depending on the product (e.g., downgrade plastic, pyrolysis oil, and refuse plastic fuel) that is produced (Kim et al., 2020; Krauklis et al., 2021; Shaha et al., 2020; Yaqoob et al., 2021). Methods to recycle plastic waste are classified into material, chemical, and thermal types (Zhuo and Levendis, 2014). They have very different capital and operating costs according to the throughput of the plastic waste of each method (Huang et al., 2002). Therefore, to improve plastic waste recycling, it is crucial to derive optimal sorting and recycling strategy for plastic waste that indicate which plastics will be sorted to be recycled and how the plastic will be recycled according to each recycling method considering economic feasibility.

Conclusion

     This study found an optimal strategy to sort and recycle plastic waste as a renewable energy resource for maximizing economic feasibility and mitigation of environmental pollution caused by landfilled plastic and air pollutants according to incineration of plastic. This study makes two major contributions to the literature. First, to the best of the author’s knowledge, it is the first attempt to optimize the plastic waste sorting and recycling system by deriving an optimal sorting and recycling strategy to improve the recycling of for plastic waste as a renewable energy resource maximizing economic feasibility and mitigating of environmental pollution. Also, the results allow us to increase the recycling of plastic waste by maximizing the overall profit of the plastic waste sorting and recycling system. In the derived optimal sorting and recycling strategy, HDPE is recycled to produce downgrade plastic; LDPE, PP and PS are recycled as pyrolysis oil; and PET is recycled to produce refuse plastic fuel. The derived optimal case can increase overall profit by ∼ 3,137% compared to CCS, and 492% compared to CCJ, and also emission of air pollutants. Thus, this study provides valuable insight into the many recycling industries of waste plastics to achieve clean production, cost-effectiveness, and environmental protection. In many literatures, strategies such as operating condition optimization were proposed to reduce the cost of each sorting method. Thus, in further study, it is crucial to consider the detailed proposed strategies in deriving the optimal solution to maximize economic feasibility.

Abstract

This study aims to examine the effect of the environmental accounting strategy on sustainability performance and explore waste management as a mediation between environmental accounting strategy and the sustainability performance of Micro, Small and Medium Enterprises (MSMEs). Research data was collected from 194 MSMEs in East Java Indonesia through online and offline questionnaires. The data analysis is performed with PLS-SEM. The results of the study found that the MSME’s environmental accounting strategy had an effect on sustainability performance, and it was proven that MSME’s waste management mediated the effect of environmental accounting strategy on MSME sustainability performance. The originality of this research is the development of research instruments, which combine from various sources from previous researchers, GRI standards and Indonesian Government Regulations so that they can contribute Environmental Management Accounting literature and practical contributions to MSMEs and related institutions in determining sustainability performance strategies. This research implication supports the goals of the Indonesian Government’s Sustainability Development Goals (SDGs) regarding SDGs Goal number 12 Responsible consumption and production. The government needs to establish a waste management policy to improve environmental problems. The implications of future research can collect larger data and can compare the MSMEs between emerging countries. Also, MSMEs need to establish strategic Environmental Accounting so that it has an impact on sustainability performance.

Introduction

Companies produce goods or services using raw materials and other materials in the production process. As a result, it impacts material waste, product, and packaging waste. The impact on economic sustainability can reduce sales and operating profits because consumers prefer environmentally friendly products. The impact on environmental sustainability not only can reduce environmental damage such as soil and water pollution and increased global warming but also decrease in employee welfare along with a decrease in operating profit.

Moreover, management’s understanding and knowledge of environmental accounting strategies and waste management are essential in achieving business sustainability in companies, including Micro, Small, and Medium Enterprises (MSMEs). The negative impacts of MSMEs include environmental pollution from production waste. As many as five industries are the biggest producers of B3 (Toxic Hazardous Materials) waste in Indonesia, namely: the metal, chemical, electricity, sugar, and paper industries. As stated by the Deputy Chairperson of Investment in East Java, Turino Junaidi, said that the amount of MSME waste is large, but the level of investment for the waste treatment industry is still small (www.kompasiana.com). For example, from 71 SMEs making tofu in Jombang, almost all of the soybean waste is disposed of together on village roads before finally being dumped into the river. As a result, it polluted the environment in three villages and even polluted surface water and well water. (www.jatim.kompas.tv/article/126221). Therefore, the environmental problems are mostly caused by the impact of economic and social activities of companies, including Micro, Small Medium Enterprises (MSMEs). Polluted water sources, polluted air, deforested forests, and global warming have damaged the environment. People’s awareness demands the importance of protecting environmentally friendly production processes and being concerned with business continuity than the short-term goal of profit.

Conclusion and implication of the research

Indonesia is concerned with Green Accounting because MSMEs waste is quite high and poor waste management. The East Java government has the second largest MSMEs in Indonesia and has a problem with industrial waste. However, it does not take maximum responsibility for product waste and an impact on low sustainability performance. This indicates the need for an Environmental Accounting strategy to support policies to minimize environmental costs related to environmental prevention costs for waste reduction employee training, environmental prevention costs for waste recycling training, environmental detection costs for environmentally friendly product inspection, internal failure costs for waste treatment and failure costs. external for cleaning polluted environment. This research implication supports the goals of the Indonesian Government’s Sustainability Development Goals (SDGs) regarding SDGs Goal number 12 Responsible consumption and production. The government needs to establish a waste management policy to improve environmental problems. Therefore all parties, namely: entrepreneurs including MSMEs, government, private sector, communities including financial institutions have the same responsibility to carry out activities and run a business with due regard to production that is responsible for the environment and society.

Abstract

Introduction

Wastewater in area of focus

Nanotechnology in water purifcation

Nano‑adsorption

Microbial agent

Nanocomposites

Types of nanocomposites

Synthesis modes for nanocomposites

Graphene oxide‑based composites as a disinfectant

Zinc oxide nanocomposites as disinfectant

Copper oxide nanocomposites

Silver/silver oxide nanocomposites

Titanium oxide nanocomposites

Discussion

Conclusion

References

Abstract

     Water is crucial for the existence of life. The world, however, is facing a global water crisis. There are variety of microorganisms, gases and other toxins responsible for water contamination. Various types of nanomaterials exist that have enormous potential to treat contaminated water (water containing metal toxins or specific organic or inorganic impurities) due to their unique properties such as a high surface area and their ability to work effectively even at low concentrations. In recent years, scientists have been giving considerable attention to the application of nanocomposites for water purification, wastewater treatment, microorganism elimination, chemical contaminants, heavy metals removal and so forth. The incorporation of different nanofillers such as carbon nanotubes, graphene oxide, 2D materials, zinc oxide, titanium dioxide, copper and silver nanoparticles into polymeric materials has facilitated important advances, such as suppressing the accumulation of pollutants and foulants, improving the hydrophilicity, increasing the efficiency and improving the mechanical properties. This review discusses leading advances in the development of nanocomposites for antimicrobial and wastewater treatment with the aim of providing an improved understanding of nanocomposites and their applications in antimicrobial and wastewater treatment.

Introduction

     Water is a basic requirement for human life. However, we are far from meeting global requirements for clean water, and this issue will continue to grow over the time (Hillie and Hlophe 2007; Elwakeel et al. 2020b). The demand of clean drinking water is rising as a result of the deterioration of water quality, global climate change and population growth (Tchobanoglous et al. 1991; Elwakeel et al. 2020d). Emissions of organic dyes and heavy metal ions from the paper, leather and textile industries are a serious problem, as they are potentially mutagenic and carcinogenic. To meet environmental requirements, wastewater contaminated with these organic and inorganic species need to be treated before being discharged (Santhosh et al. 2016; Elwakeel et al. 2021). Heavy metals are widely used in various industries for many purposes, including mining and pigment production. Synthetic dyes are also an important type of pollutant, and their sources for water contamination include the textile, pulp and paper, tinting, printing, painting and tanning industries. The removal of dye from such wastewater is a challenging task, as pigments and synthetic dyes are biodegradation-resistant and remain in the environment for a long time. The destruction and handling of organic dyes is therefore an important issue, and a cost-efective method for removing dye substances from wastewater has been developed (Santhosh et al. 2016; Elwakeel et al. 2018).

Conclusion

     This paper explores the existing nanocomposites used to extract heavy metal ions and dyes from wastewater as efective adsorbents. This article addressed recent developments in nanomaterials as economical and environmentally sustainable water purifcation adsorbents. This review highlights fve commonly used nanomaterials/nanoparticles that are used in most existing nanocomposites. In this review, we concluded that TiO2-based nanocomposites have been used for photodegradation activity by most of the researchers in the literature. Silver-based nanocomposites are mostly used for antimicrobial activity. Silver and GO-based nanocomposites were used for the removal of green dye, anionic dye and Cu(II). Copper-based nanocomposites are mostly used for adsorption and photodegradation activity. Zinc oxide nanocomposites are used for adsorption, antimicrobial and photodegradation activity. Finally, we concluded that GO also greatly contributes to the improvement of other materials’ efciency. Further, much needs to be done to control the two-dimensional GO sheets for advanced technologies in the future. There are many challenges and obstacles associated with handling wastewater, and many precautions are required to prevent environmental and health problems. Therefore, new modern wastewater treatment equipment should be versatile, low-cost and commercially efective.

Abstract

1. Introduction

2. Literature review

3. Integrated analytical framework for sustainability analysis of supply chain management

4. Results

5. Conclusions

Disclosure statement

References

Abstract

     With the increasing importance of air pollutant emissions to the platform economy and green supply chain management, it is essential to analyse the trend and correlation between particulate matter emissions and supply chain statistics. Typical approaches do not integrate particulate matter prediction with the sustainability analysis, and suffer from common issues such as low classification accuracy and unstable prediction performance. In this study, we propose an integrated analytical framework for sustainability analysis of supply chain management through particulate matter emissions prediction. Specifically, we performance trend and correlation analysis between particulate matter emissions (PM2.5 and PM10) and supply chain statistics in Beijing of China. We combine the boosting algorithm and neural network method to predict particulate matter emissions. Experimental results show that our prediction model achieved high performance. Sustainability analysis shows that the steady growth of the supply chain operations is accompanied by decreasing air pollutant emissions in China.

Introduction

     Today, human society is facing very severe environmental and resource problems. The green and sustainable supply chain are the concrete manifestations of sustainable development strategies that comprehensively consider these two issues in platform economy management. In recent years, continued urbanisation and industrialisation, particularly in developing countries, has led to severe deterioration in air quality and a rapid increase in the degree of contamination (Shi and Yu 2020). Air pollution has substantially affected the living environment of the human population and endangered health (Stieb et al. 2019). The United Nations (UN) issued Sustainable Development Goals (SDGs) in 2015, serving as a blueprint for building a more sustainable future across the globe. There are totally 17 goals in SDGs, addressing issues in economic, environmental, and social areas. These goals are interrelated and expected to be fulfilled by 2030 (2015). PM2.5 emissions have an adverse effect on public health (Yin, Pizzol, and Xu 2017). At present, many countries attach great importance to inhalable total suspended particulates that cannot be blocked by the human upper respiratory tract, especially inhalable aerosol particles with sizes less than 2.5 μm. It is necessary to arouse the stakeholder

Conclusions

     In this paper, an integrated analytical framework targeting sustainability analysis of supply chain management through particulate matter emissions prediction has been proposed. Specifically, we firstly collect and preprocess the particulate matter emission data and supply chain statistics in Beijing of China, then we conduct correlation analysis between air pollutant concentrations and supply chain statistics to uncover the intrinsic associations. Secondly, we combine the boosting ensemble meta-algorithm and neural network method for particulate matter concentration forecasting. The boosting algorithm is used to train a set of individual subnets to improve the efficiency of prediction, and afterwards, the output results of individual subnets are weighted for acquiring the final prediction results. Finally, we perform an analysis on sustainability between air pollutant emissions and supply chain statistics after obtaining the particulate matter prediction results.

     This analytical framework is able to perform sustainability analysis with accuracy and provide reliable insights for the legislation and implementation of green supply chain management. The forecasting of particulate matter emissions conveys basis and justifications for policy-makers to enforce the environmental protection measures associated with air pollution and design efficient policies with the aim of improving the air pollutant management of the supply chain, which will further lead to an improved public health environment, especially in economically developed areas. Because this study mainly targets the prediction of PM2.5 and PM10 concentrations, it cannot comprehensively reveal the geographical distribution of air pollution. There are various factors that affect air quality, and a regression model can be established to predict PM2.5 and PM10 distributions more comprehensively and to determine the key influential factors, which would be important for formulating economic development strategies and implementing environmental protection mechanisms.

Abstract

1. Introduction

2. Methods and Materials

3. International Perspective on Air Pollution

4. General and Respiratory Disease Hospitalization and Mortality Rates

5. Children

6. Adults

7. COVID-19 Pandemic

8. Social Awareness of Air Pollution in Poland

9. Limitations and Future Perspectives

10. Conclusions

Abbreviations

References

Abstract

     According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles’ awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.

Introduction

     Ambient air pollution is one of the most significant environmental issues affecting health and wellbeing. It is linked to increased mortality from cardiovascular and respiratory diseases, including lung cancer and chronic obstructive pulmonary disease (COPD), shortening life expectancy [1]. It is estimated that in Europe in 2019, about 307,000 premature deaths were caused by chronic exposure to fine particulate matter with a diameter of 10 micrometres or smaller (PM10) and to coarse particulate matter with a diameter of 2.5 micrometres or smaller (PM2.5) [2]. In addition, about 40,000 premature deaths were attributed to chronic nitrogen dioxide (NO2) exposure [2].

     According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland [3]. Moreover, Polish cities are among the urban areas with the highest estimated PM mortality burden [4]. Despite a consistent decrease in annual outdoor PM concentrations in the most polluted Polish cities in the recent decade, current values still do not meet the World Health Organisation (WHO) guidelines [5,6].

Conclusions

     In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality and hospitalization rates as well as a higher prevalence of respiratory symptoms (wheezing, dyspnoea attacks, chronic cough) and respiratory diseases, including bronchitis, asthma, rhinitis, lung cancer and COVID-19 infections. Reduced FEV1 and FVC in spirometry tests are also observed. Infants, children, adolescents as well as adults are affected by worse air quality. Living in the proximity of high traffic areas exacerbates respiratory health problems.

     There is ample evidence that the course of asthma and bronchitis is exacerbated in areas with high ambient air pollution, while the indicators of subjective quality of life in asthmatic patients are lower. In atopic subjects, air pollution seems to sensitise the body and trigger an excessive response when combined with the usual allergen. There is also some evidence that higher concentrations of PM2.5, PM10, SO2, NO2 and ozone may facilitate the spread and infectiousness of SARS-CoV-2.