The form of the species richness-productivity relationship (SRPR) is both theoretically important and contentious. In an effort to distill general patterns, ecologists have undertaken meta-analyses, within which each SRPR data set is first classified into one of five alternative forms: positive, humped (unimodal), negative, U-shaped (unimodal), and no relationship. Herein, I first provide a critique of this approach, based on 68 plant data sets/studies used in three meta-analyses published in Ecology. The meta-analyses are shown to have resulted in highly divergent outcomes, inconsistent and often highly inappropriate classification of data sets, and the introduction and multiplication of errors from one meta-analysis to the next. I therefore call on the ecological community at large to adopt a far more rigorous and critical attitude to the use of meta-analysis. Second, I develop the argument that the literature on the SRPR continues to be bedeviled by a common failing to appreciate the fundamental importance of the scale of analysis, beginning with the confusion evident between concepts of grain, focus, and extent. I postulate that variation in the form of the SRPR at fine scales of analysis owes much to artifacts of the sampling regime adopted. An improved understanding may emerge from combining sampling theory with an understanding of the factors controlling the form of species abundance distributions and species accumulation curves.
Low carbon dioxide (CO ) emissions are the foundation on which to realize the sustainable development of a green China. Recently in Beijing, the capital of China, serious environmental pollution-climate anomaly, severe haze and human sub-health have been accorded more importance. This study examines the energy-related CO emissions generated by Beijing industries from 2000 to 2010 by using an input–output analysis method. The direct, indirect and total CO emissions of sectors in Beijing were calculated. In addition, structural decomposition analysis (SDA) was conducted to evaluate the driving factors from the perspective of technology, sectoral connection, economic structure and economic scale. The results show that the growth rate of sectoral CO emissions in Beijing has drastically increased during this time with a moderate decline during 2007–2010. The metal and non-metal mining industries, the electric power, gas and water supply sector and the construction industry caused the most CO emissions. The economic structure change and the rapid economic growth led to the significant increase in CO emissions growth in Beijing. Thus, optimizing the economic structure and improving the technology are important to alleviate CO emissions. Although we can currently appropriately utilize fossil fuels, further research on new energy and clean development, as well as enhanced government management strength is required to reduce CO emissions.
Energy consumption has always been a central issue for sustainable urban assessment and planning. Different forms of energy analysis can provide various insights for energy policy making. This paper brought together three approaches for energy consumption accounting, i.e., energy flow analysis (EFA), input–output analysis (IOA) and ecological network analysis (ENA), and compared their different perspectives and the policy implications for urban energy use. Beijing was used to exemplify the different energy analysis processes, and the 42 economic sectors of the city were aggregated into seven components. It was determined that EFA quantifies both the primary and final energy consumption of the urban components by tracking the different types of fuel used by the urban economy. IOA accounts for the embodied energy consumption (direct and indirect) used to produce goods and services in the city, whereas the control analysis of ENA quantifies the specific embodied energy that is regulated by the activities within the city’s boundary. The network control analysis can also be applied to determining which economic sectors drive the energy consumption and to what extent these sectors are dependent on each other for energy. So-called “controlled energy” is a new concept that adds to the analysis of urban energy consumption, indicating the adjustable energy consumed by sectors. The integration of insights from all three accounting perspectives further our understanding of sustainable energy use in cities.
This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system.
Waste electrical and electronic equipment (WEEE) is one of the fastest growing waste streams, worldwide. In addition to the increasing amount, WEEE consists of numerous toxic, precious and scarce metals which makes its recycling and safe disposal an important environmental issue. Switzerland has a well-established recycling system operating since 1992. With 15 kg of WEEE collected per inhabitant in 2011, Switzerland is one of the leading countries in collection. However, small electronic devices and IT and telecommunication equipment that do not constitute a significant mass in overall WEEE pose greater challenges to collection and recycling due to their size and dissipative structure. Among these categories, laptops and mobile phones stand out with increasing penetration rate, decreasing lifetime, and complex composition with high concentrations of precious metals in relatively small volumes. This study investigated the recycling of WEEE in Switzerland with particular focus on material flows of laptops and mobile phones as well as copper, silver, gold, and palladium originated from these products in 2011. Material flow analysis revealed collection rate for laptops and mobile phones as 35 and 37% and treatment rates as 28% and 15%, respectively. The overall recycling rates for copper, silver, gold, and palladium in laptops were estimated as 21, 13, 14, and 14%, respectively. As a result of lower treatment rate for mobile phones the recycling rates were found as 12% for copper, 7% for silver 8% for gold and palladium. In addition to the quantitative assessment of the recycling programme’s performance, Structural analysis was carried out to understand the underlying socio-economic, technical, and political elements that are influential in this case. The results suggest that external factors such as metal prices and criticality of metals have large influence on material flows. By coupling stakeholders' conceptualization of the system with material flows, this study strives to provide a comprehensive interpretation of the system for strategic management of WEEE in Switzerland.
In the third Joint Danube Survey (JDS3), emerging organic contaminants were analysed in the dissolved water phase of samples from the Danube River and its major tributaries. Analyses were performed using solid-phase extraction (SPE) followed by ultra-high-pressure liquid chromatography triple-quadrupole mass spectrometry (UHPLC-MS-MS) and gas chromatography–mass spectrometry (GC–MS). The polar organic compounds analysed by UHPLC-MS-MS were 1H-benzotriazole, methylbenzotriazoles, carbamazepine, 10,11-dihydro-10,11-dihydroxy-carbamazepine, diclofenac, sulfamethox-azole, 2,4-D (2,4-dichlorophenoxyacetic acid), MCPA (2-methyl-4-chlorophenoxyacetic acid), metolachlor, cybutryne (irgarol), terbutryn, DEET ( , -diethyl- -toluamide), and several perfluoroalkyl acids (C –C ; C = perfluorooctanoic acid (PFOA)) and perfluorooctansulfonic acid (PFOS). In addition, several organophosphorus flame retardants were analysed by GC-MS. The most relevant compounds identified in the 71 water samples, in terms of highest median and maximum concentrations, were 1H-benzotriazole, tris(1-chloro-2-propyl)phosphate (TCPP), methylbenzotriazoles, carbama-zepine and its metabolite, DEET, sulfamethoxazole, tris(isobutyl)phosphate (TiBP), tris(2-chloroethyl)phosphate (TCEP), PFOA, PFOS and diclofenac. The concentrations of these compounds in the samples were generally below the environmental quality standard (EQS) threshold values, with the exception of PFOS, the concentration of which exceeded the annual average water EQS limit of 0.65 ng/L along the whole river, and also exceeded the fish biota EQS of 9.1 μg/kg. In addition, the proposed EQS for diclofenac, of 0.1 μg/L, was exceeded in the Arges River in Romania (255 ng/L).
Significant energy flows embodied in international trade have evolved into a complex interconnected flow network. Therefore, this study applies a variety of complex network analysis tools to uncover the structure of embodied energy flow network (EEFN) at global, regional and national level, based on environmentally extended input–output analysis (EEIOA). At global level, small-world nature has been found, implying the economies are highly connected through embodied energy transfer. EEFN is proved to be a heterogeneous network due to the scale-free power-law distribution of degree/strength. At regional level, 4 communities are detected and members in the same regional cooperative organizations, such as EU, ASEAN, NAFTA and AU, tend to be classified into the same community, indicating that EEFN embodies the characteristics of regionalization and multi-polarization. At national level, some key economies, such as USA, China and Germany, are always at the forefront of network-based centrality measures and EEIOA-based accountings. Furthermore, the security of embodied energy supply is evaluated for each economy. Consequently, policy implications of the results are discussed, which could provide additional insights for policy formulation to enhance energy security.
This paper presents a generalized framework to construct composite indicator, which can be used in static and dynamic analysis. By grouping DMUs (decision making units) first, the proposed approach is more flexible to derive weights for entities featuring diverse characteristics. A more neutral set of weights can be obtained through investigating the lower and upper bound of possible weights. Subsequently, we introduce a slack-based composite indicator from the perspective of distance function, which facilitates studying entities' improvement potential in sub-indicators. Furthermore, the slacks-based composite indicator is combined with the Malmquist index to conduct dynamic assessment, aiming to quantify the evolvement of composite indicator over time and the underlying driving forces. To illustrate the usefulness of the proposed approach, it is applied to construct the Sustainable Energy Index for 109 countries worldwide in 2005–2010. Our results show that the high-income country group has the best sustainable energy performance among all the three country groups in 2010. The dynamic assessment indicates the worldwide sustainable energy development level declined during 2005–2010, and the efficiency change was the main negative driving force. More discussions and implications are presented in the paper.
Corrosion scales and deposits formed within drinking water distribution systems (DWDSs) have the potential to retain inorganic contaminants. The objective of this study was to characterize the elemental and structural composition of extracted pipe solids and hydraulically-mobile deposits originating from representative DWDSs. Goethite (α-FeOOH), magnetite (Fe O ) and siderite (FeCO ) were the primary crystalline phases identified in most of the selected samples. Among the major constituent elements of the deposits, iron was most prevalent followed, in the order of decreasing prevalence, by sulfur, organic carbon, calcium, inorganic carbon, phosphorus, manganese, magnesium, aluminum and zinc. The cumulative occurrence profiles of iron, sulfur, calcium and phosphorus for pipe specimens and flushed solids were similar. Comparison of relative occurrences of these elements indicates that hydraulic disturbances may have relatively less impact on the release of manganese, aluminum and zinc, but more impact on the release of organic carbon, inorganic carbon, and magnesium.
Organic aerosols were studied at the molecular level in 14 coastal and inland mega-cities in China during winter and summer 2003. They are characterized by the abundant presence of n-alkanes (annual average, 340 ng m(-3)), fatty acids (769 ng m(-3)), sugars (412 ng m(-3)), and phthalates (387 ng m(-3)). In contrast, fatty alcohols, polyols/polyacids, lignin and resin products, sterols, polycyclic aromatic hydrocarbons (PAHs), and hopanes were detected as relatively minor components. n-Alkanes show a weak odd/even carbon predominance (CPI = 1.1) and PAHs show a predominance of benzo(b)fluoranthene, suggesting a serious contribution from fossil fuel ( mainly coal) combustion. Their concentrations ( except for phthalates and polyols/polyacids) were 2-15 times higher in winter than summer due to a significant usage of coal burning and an enhancement of atmospheric inversion layers. Phthalates were found to be more abundant in summer than winter, probably due to enhanced vaporization from plastics followed by adsorptive deposition on the pre-existing particles. Concentrations of total quantified compounds are extremely high (similar to 10 mu g m(-3)) in the midwest (Chongqing and Xi'an) where active industrialization/urbanization is going on. This study shows that concentrations of the compounds detected are 1-3 orders of magnitude higher than those reported from developed countries.