环境科学与工程 | SCI期刊专刊信息5条

全文截稿: 2019-08-15

影响因子: 4.61

中科院JCR分区:

  • 大类 : 环境科学与生态学 - 2区

  • 小类 : 环境科学 - 2区

网址: https://www.journals.elsevier.com/science-of-the-total-environment

Authors are invited to submit papers related to the following topics:

This special issue would represent novel work that is of general interest for a broad audience of the journal given the implications of the environmental changes and its relationship with humankind across all biomes. The existence of a worldwide environmental crisis, dwindling natural sources and increasing concern over the uncertainty of fossil reserves, climate change among all key spheres including atmosphere, hydrosphere, biosphere, lithosphere, and anthroposphere, global warming and energy insecurity all have led to a resurgence in the development of environmentally-responsive greener strategies. In this context, research is underway around the globe to (re)-search renewable bio-resources to produce sustainable energy along with industrially-relevant commodity chemicals. Considering the proposed scenario, natural sources based integrated transition to meet bio-economy challenges and opportunities have the following justifications:

(i) to safeguard the natural ecosystem

(ii) to circumvent or diminish the current price hike

(iii) to provoke awareness on the worldwide climate issues

(iv) to stimulate the greener development of regional and rural areas

(v) to diminish the activities which cause greenhouse gasses emission

(vi) to strengthen and diversify the bio-renewable-based energy sources

(vii) to circumvent an over dependency on petrochemicals and/or petro-sources

(viii) to decrease/circumvent the over-consumption of the oil, gas, coal and other potential minerals

全文截稿: 2019-08-30

影响因子: 5.651

中科院JCR分区:

  • 大类 : 环境科学与生态学 - 1区

  • 小类 : 工程：环境 - 2区

  • 小类 : 环境科学 - 2区

网址: https://www.journals.elsevier.com/journal-of-cleaner-production

City organizes and sustains itself by circulating high density of resource flows in production and consumption activities. However, there exist serious conflicts between increasing demand and waning carrying capacity of the urban area due to rapid urbanization (Chen, 2015). Urbanization also results in a rapid increase in energy consumption through: the urban spatial expansion, where urban sprawl has increased energy consumption in building sector and the transport sector; urban motorisation, which induces energy-intensive transportation; and the rising quality of energy-intensive lifestyles (Bai et al., 2014).

As such, there exists a wide concern: how can we encourage a greener and smarter growth in line with sustainable urbanization? For this sake, tracking material and energy flows that enter into, exchange within and finally depart from the city will clue on how they build the urban fabric and provide effective solutions for urban eco-environmental problems (Chen and Chen, 2015). Since the cities have special characteristics including structures, processes, and functions, it is necessary to use effective methodologies based on interdisciplinary issues to model the whole system consisted of interactive socio-ecological components with a nexus approach (Chen, 2015; Chen and Lu, 2015). It also requires collective efforts from the technological, economic, political and public units to go for a greener city (Zhao and Zhang, 2018). Positive changes in all urban sectors such as building, business, commercial, transport, consumption and energy are indispensable. In addition, the changes in people’ attitudes and actions will eventually change the way how cities are designed, constructed, managed and sustained (Bettencourt, 2010).

Given the fact that technological, economic, political and public issues are entangled into the complex urban systems, it is increasingly awared that any improvement from a single aspect, e.g., water, energy, or carbon, may not effectively achieve the expected results, but have to think about the nexus of these aspects (Chen et al., 2018). Researchers have spent increasing efforts on exploring the interrelation between different issues and thus provided insightful solutions accordingly (Fang and Chen, 2017; Fang et al., 2019). In the meantime, advanced technologies for interpreting complex systems, such as various data processing technologies, artificial intelligence and deep leanring, complex system theories, multi-objective dynamic optimization techniques, have been applied to the practice of green and smart urbanization (Wang and Chen, 2018).

The Special Issue, aims to extending our understanding about the nexus between energy and the environment in order to provide innovative solutions to sustainable urban development.

Upon the target of JCLP, the special issue intends to establish a platform for addressing and discussing theoretical and practical innovative solutions towards a greener urbanization, which include progresses in technology, system, production, consumption, institution and society. In accordance with the high academic standards promoted by the JCLP, this special issue focuses on, but is not limited to, the following topics:

Urban energy-water-air nexus

Urban Energy-Transport Nexus

Nexus of Urban Land Use and Energy

Energy-Air Quality- Health Nexus

Energy-water-waste Nexus

Renewable energy supply and management for urban sectors

Green urban building design and construction

Greener urban transportation

Energy and material metabolism

Energy coversion and consumption for sustainable urbanization

全文截稿: 2019-08-31

影响因子: 5.651

中科院JCR分区:

  • 大类 : 环境科学与生态学 - 1区

  • 小类 : 工程：环境 - 2区

  • 小类 : 环境科学 - 2区

网址: https://www.journals.elsevier.com/journal-of-cleaner-production

1. Introduction

With the current increase in environmental awareness, green manufacturing research and application attracts considerable attention. The aim of green manufacturing is to minimize environmental damage and energy waste while guaranteeing the quality and function of products and improving the profit of manufacturing enterprises. It comprehensively considers environmental impacts and resource efficiency to ensure economic and social benefits and the sustainability of industrial enterprises. New manufacturing technologies and initiatives, such as digital manufacturing, additive manufacturing, smart manufacturing, and Internet of Things, provide new opportunities for green manufacturing, but also add complexity. As a significant part of green manufacturing, green scheduling is a special category of shop and production scheduling problems where energy savings, resource consumption reduction, and emission reduction are considered. Efficient green scheduling can provide significant benefits in both reduced costs and lessened environmental impact.

In recent decades, increases in the price and demand for fossil energy and the rising problem of global climate change have resulted in greater efforts directed towards minimizing energy and resource consumption. According to the US Energy Information Administration, the industrial sector accounts for one-half of the world’s total energy consumption, which has almost been doubled over the last 60 years. In China since 1978, the industrial sector contributes about 40% of GDP, but consumes 67.9% of total national energy and emits 83.1% of total national carbon dioxide. However, most of the existing work on reducing energy consumption only focuses on developing more energy efficient machines or processes, instead of improving the operational process. At Toyota Motor Corporation, recent research shows that more than 85% of energy is consumed by non-machining operations, which are not directly related to the actual production of parts. To tackle this issue, more attention should be paid to developing efficient operational methods to implement a significant reduction of energy.

This Special Volume (SV) aims to address green scheduling problems and explore different approaches for energy savings and emission reductions. Up until now, the existing studies about green scheduling only considered a few simple problem characteristics, such as a single machine, flow shop scheduling, and so on. Complex constraints, including multiple resource constraints, flexible scheduling, and uncertainty situations should also be considered for the practical application of green scheduling. In addition to energy consumption and emission problems related to machine operations, design, packing, transportation and logistics, and recycling procedures should also embody the concept of “green scheduling.” Although green scheduling has become a research hotspot in the field of job scheduling, its practical applications are still limited. Advanced theoretical results have not yet been verified and applied to actual systems.

This SV is open to all engineering disciplines and a wide range of research topics addressing green scheduling. Papers are also accepted where the primary focus is on green scheduling in general. This SV attempts to bring together researchers, industrial engineers, and administrators by highlighting state-of-the-art theories, methods, and technologies, as well as ideas to effectively integrate optimization into the whole production process.

2. Topical areas

Theme 1: Green scheduling problems and its extensions

Most of the existing studies on green scheduling are aimed at traditional workshop scheduling problems, such as single machines, parallel machines, and so on, which is relatively simple. Green scheduling problems are faced by various industries. Several complex situations, such as multiple resource constraints, machine failures, cooperative manufacturing, and online scheduling can be studied to more accurately model practical applications. Moreover, models and calculations of energy-saving measures are also very important to realize energy savings and emission reductions in terms of different specific applications. With this in mind, the following research ideas are welcomed:

• Research review on green scheduling,

• Definition and formulation of novel green scheduling problems, especially ones considering new manufacturing technologies, such as smart manufacturing, additive manufacturing, digital manufacturing, Internet of Things, new energy for manufacturing, etc., and business operations beyond shop floors.

• Benchmark problem research of green scheduling systems.

Theme 2: Algorithms

To satisfy the requirements of both economic and energy-saving measures, the green scheduling problem is typically modeled as a multi-objective optimization problem. This multiple objective problem requires a high-efficiency search capability in a decision-variable space and good equilibrium or collaborative capabilities in the objective space for the solving algorithm. On the other hand, the complexity, the effectiveness, and the sensitivity analysis of multi-objective optimization algorithms should be considered, as well as some special techniques such as Pareto dominance strategies, constraint satisfaction methods, analytic hierarchy processes, and so on. With this concern, the following research ideas are encouraged:

• Algorithms for green manufacturing resource planning

• Algorithms for green supply chain design and optimization

• Algorithms for green manufacturing

• Algorithms for smart green manufacturing systems

• Algorithms for unmanned green manufacturing systems

• Multi-objective optimization algorithms for green manufacturing systems

• Dynamic optimization algorithms for green manufacturing systems

• Uncertain optimization algorithms for green manufacturing systems

• Memetic algorithms for green manufacturing

Theme 3: Applications

Although some work has been conducted on green scheduling, few have adapted the academic results into practical applications. It is important to build more practical models and to specifically develop implementable algorithms for green scheduling problems by deeply analyzing the nature of different problem characteristics, such as:

• Memetic algorithms for manufacturing in practical systems

• A future vision for green scheduling systems

• Application practices of green scheduling systems

全文截稿: 2019-12-31

影响因子: 4.61

中科院JCR分区:

  • 大类 : 环境科学与生态学 - 2区

  • 小类 : 环境科学 - 2区

网址: https://www.journals.elsevier.com/science-of-the-total-environment

The rapid development of big data technology has unprecedented opportunities and challenges for dynamic environmental management. Big data, as a new form of information technology and service, is now becoming an important revolutionary industry. Through specialized “processing” of massive and complex data, it creates numerous new products and services (Song et al., 2017a). Because most human activities are closely related to the ecological environment, which contains massive data, further improvement of environmental management through effective processing and use of big data has become a key issue for managers. Compared with traditional data, big data displays the 5V Characteristics, which are Volume, Variety, Veracity, Velocity, and Valorization (Wang et al., 2017). This makes using big data technology in dynamic environmental management inevitable.

From the data source perspective, there are essential differences between big data and traditional data. World famous data management Statistical Analysis System (SAS), divides big data into three categories according to its source. The first is Streaming Data, including various data collected from the Internet, such as GIS remote sensing data, sensor data, and environmental monitoring data, among others. One of the key features of Steaming Data is the high-speed persistence, which requires processing in an almost real-time manner. The second category is Social Media Data. Social Media Data has gained increasing attention in fields such as product design and marketing, and is usually observed in unstructured or semi-structured form. The third category is Publicly Available Sources, which is available from open-source sources such as government and nonprofit organizations but has the characteristics of source uncertainty and unknown data characteristics. Because of its structured feature, streaming data is attracting more and more attention. Therefore, streaming data will become the basis for dynamic environmental performance improvement and optimization, risk identification, and trend prediction. It is of great theoretical and practical significance to use streaming data in dynamic environmental management.

The development of big data technology, especially the collection and application of streaming data, makes it possible to pay more attention to the features of complexity and instability of dynamic environmental management.Dynamic environmental management promotes the efficient use of resources and reduces the uncertain risk in decision-making (Ryberg et al., 2018). Facing the uncertain and rapidly changing ecological environment, managers urgently need new methods for dynamic improvement and optimization of environmental management, which can simultaneously evaluate environmental conditions in time, provide timely warning about environmental problems, and predict possible future environmental risks.

However, streaming data is different from traditional static data in that it has time continuity, high rapidity, time uncertainty, and other characteristics (Zhu et al., 2018). All these differences make incorporating streaming data into dynamic environmental management a challenging job. For example, using massive real-time monitoring data to evaluate dynamic environmental performance needs to solve at least the following three problems (Song et al., 2017b). First, how to sort and extract key index data from such a huge amount of information. Second, in the face of the continuous and rapid arrival of monitoring data, dynamic environmental management methods should realize the rapid evaluation of indicator variables. Third, the timeliness of acquired monitoring data should be further considered to avoid real-time data being affected by sudden factors. The above characteristics of streaming data greatly increase the complexity of dynamic environmental management.

The flow of data generated and passed at a high speed presents new challenges to environmental management, while also providing new opportunities (Knüppe & Knieper, 2016). On the one hand, the generation of streaming data technology allows managers to establish a set of early warning mechanisms for quick response and decision making, together with having full use of the data on environmental performance evaluation. On the other hand, the time-sensitivity of streaming data also provides a new platform for accurate understanding of environmental dynamics, real-time monitoring of environmental problems, and timely resolution of environmental crises.To develop a better understanding of the dynamic improvement and optimization of environmental management in the presence of streaming data, this special issue seeks high-quality original research papers, which innovatively contribute to emerging issues of streaming data-based dynamic environmental management.

全文截稿: 2020-12-15

影响因子: 4.395

中科院JCR分区:

  • 大类 : 环境科学与生态学 - 2区

  • 小类 : 生态学 - 2区

  • 小类 : 环境科学 - 2区

网址: https://www.journals.elsevier.com/ecosystem-services

Background

Ecosystem services approach, as a very attractive for capturing relations between ecosystems and human well-being, has been absorbed by various disciplines of natural, social and economic sciences. At the same time, the goal of Special Issue is to promote research topics that sharpen the conceptual scope of ecosystem services as a research field linking different perspectives and disciplines, and thus foster the integration of nature's values into governance processes.generation of knowledge on ecosystem services is less often the subject of cooperation between disciplines. Representatives of individual disciplines undertake research according to their area of interests, conceptual foundations and disciplinary perscpectives. This provides an opportunity for the development of particular disciplines, but also form the risk of decreasing of whole concept comprehensivity as a result of its fitting to individual disciplines. The goal of Special Issue is to promote research topics that sharpen the conceptual scope of ecosystem services as a research field linking different perspectives and disciplines, and thus foster the integration of nature's values into governance processes.

Special Issue contents

The Special Issue will be focused on new achievements in crossing the disciplinary barriers in ecosystem services research, including the methods, tools, models and implementation.

We will consider papers that move beyond disciplinary bounduaries and integrate the biophysical, socio-cultural and economic dimensions of ecosystem services. Within this frame, the themes can include:

Theoretical framework for transdisciplinary approach;

Identification of comprehensive sets of ecosystem services indicators for individual ecosystem types, e.g. agroecosystems, forest ecosystems, urban ecosystems, freshwater ecosystems and marine ecosystems;

Optimal degree of data detail for analysis of ecosystem services at the national, regional and local scales;

Specificity of ecosystem services on the landscape scale;

Ecosystem services bundles, synergies and trade-offs.

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