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Alkylated PAHs (APAHs) have been shown to be more toxic and persistent than their non-alkylated parent compounds. However, little is known about the extent of soil contamination by these pollutants. To help understand agricultural soil pollution by these compounds at a regional scale, a total of 18 methylated PAHs (MPAHs, a major class of APAHs) in 243 soil samples were analyzed. These soil samples were collected from 11 sites in the Yangtze River Delta (YRD) region, a representative fast developing area in China. The total concentration of MPAHs (∑18MPAHs) ranged from 5.5 to 696.2 ng/g dry soil, with methylnaphthalenes (M-NAPs) and methylphenanthrenes (M-PHEs) accounting for more than 70% of the compositional profile. Relatively high concentrations of ∑18MPAHs were found in Jiaxing and Huzhou areas of Zhejiang province, as well as on the border between the cities of Wuxi and Suzhou. Different MPAH groups showed dissimilar spatial distribution patterns. The spatial distribution of lower molecular weight MPAHs was related to agricultural straw burning and emissions/depositions from industrial activities, whereas that of higher molecular weight MPAHs was much more a function of the total organic carbon (TOC) content of soil. Although coal, biomass (crop straw and wood), and petroleum combustion were identified to be the major emission sources for most of the sampling sites, the areas with relatively severe pollution with ∑18MPAHs resulted from the localized hotspots of petroleum leakage. Isomeric MPAHs with methyl group substituted at 2- (β) position exhibited significantly higher concentrations than those substituted at 1- (α) position. Results of this work help to understand soil pollution by MPAHs, and are useful for designing effective strategies for pollution control so as to ensure food safety in areas with fast economic growth.

This paper aims to develop a green building meta-model for a representative passively designed high-rise residential building in Hong Kong. Modelling experiments are conducted with EnergyPlus to explore a Monte Carlo regression approach, which intends to interpret the relationship between input parameters and output indices of a generic building model and provide reliable building performance predictions. Input parameters are selected from different passive design strategies including the building layout, envelop thermophysics, building geometry and infiltration & air-tightness, while output indices are corresponding indoor environmental indices of the daylight, natural ventilation and thermal comfort to fulfil current green building requirements. The variation of sampling size, application of response transformation and bootstrap method, as well as different statistical regression models are tested and validated through separate modelling datasets. A sampling size of 100 per regression coefficient is determined from the variation of sensitivity coefficients, coefficients of determination and prediction uncertainties. The rank transformation of responses can calibrate sensitivity coefficients of a non-linear model, by considering their variation obtained from sufficient bootstrapping replications. Furthermore, the acquired meta-model with MARS (Multivariate Adaptive Regression Splines) is proved to have better model fitting and predicting performances. This research can accurately identify important architectural design factors and make robust building performance predictions associated with the green building assessment. Sensitivity analysis results and obtained meta-models can improve the efficiency of future optimization studies by pruning the problem space and shorten the computation time.

Optimizing the design of water distribution systems often faces difficulties due to continuous variations in water demands, pressure requirements, and disinfectant concentrations. The complexity of this optimization even increases when trying to optimize both the hydraulic and the water quality design models. Most of the previous works in the literature did not investigate the linkage between both models, either by combining them into one general model or by selecting any representative solution to proceed from one model to another. This work introduces an integrated two-step framework to optimize both designs while investigating the reasonable network configuration selection from the hydraulic design view before proceeding to the water quality design. The framework is mainly based on a modified version of the multi-objective particle swarm optimization algorithm. The algorithm’s first step is optimizing the hydraulic design of the network by minimizing the system’s capital cost while maximizing the system’s reliability. The second step targets optimizing the water quality design by minimizing both the total consumed chlorine mass and the accumulated differences between actual and maximum chlorine concentrations for all the network junctions. The framework is applied to Safi Network in Yemen. Three scenarios of the water quality design are proposed based on the selected decision variables. The results show a superior performance of the first scenario, based on optimized 24-h multipliers of a chlorine pattern for a flow-paced booster station, compared to the other scenarios in terms of the diversity of final solutions.

The ageing population tends to be seen as a burden of cities’ future development. Thus, the public funds for older residents’ wellbeing are at risk of being cut back under the economic austerity due to the prevalent neoliberalism policy atmosphere. However, some cities set good examples to turn their older citizens into active contributors to sustainable urban development (SUD) by developing age-friendly cities and communities (AFCC). Taking Hong Kong as an example, this study aims to raise a strategy for policymakers, especially at the municipal level, to incorporate the concept of AFCC in SUD. Data were retrieved for our analysis from a published report of the Hong Kong Public Policy Research Fund project. A total of 15 AFCC and SUD policy factors were identified by using factor analysis. The correlations between these policy factors were evaluated and visualised in a synergetic effect network. According to the network, this study indicates that developing the silver hair market can be a suitable entry point to realise SUD by adopting an AFCC development. Isolation prevention, social sustainability and low-energy-consumption development are the supportive policy factors for the silver hair market. Specifically, respect, discrimination prevention, communication and information, age-friendly facilities, environmental safety and public transportation accessibility are five AFCC policy factors incorporated in the policy integration to enhance older residents’ wellbeing further. This study is an innovative attempt to develop a comprehensive model for the synergy between sustainable urban development and an age-friendly city and community using a correlation network. This study also provides a reference for other city governments to respond to population ageing positively.

A prior requirement to the design of any solar-based conversion systems is the knowledge of optimum orientation and tilt surface at which peak solar energy can be collected. In many parts of the world, however, the solar radiation data for the surfaces of interest are not always available. This paper presents a numerical approach to calculate the solar radiation on sloped planes by integrating the measured sky radiance distributions. The annual total solar yield at different sloped surfaces facing various orientations and monthly solar radiations at the optimal tilt surface and three vertical planes facing east, south, and west were determined. The energy outputs and efficiencies were simulated using a computer package. The environmental benefits in terms of greenhouse gases reductions and cost implications were also considered. The findings provide technical information for engineers to design and evaluate photovoltaic (PV) systems which could contribute to the environmental, energy, and economic aspects.

Durante la última década, los principales países del sur de Asia (Pakistán, India y Bangladesh) han utilizado efectivamente la electricidad eólica para evitar futuras dificultades energéticas. Sin embargo, la industria eólica está siendo influenciada por una amplia gama de factores. El objetivo de este estudio es desarrollar un modelo de cadena de valor para la industria de la energía eólica del sur de Asia, analizar los factores internos y externos para analizar la viabilidad de la condición actual y la hoja de ruta futura para fomentar el sector de la energía eólica mediante la adopción del modelo de Fortalezas, Debilidades, Oportunidades y Amenazas (FODA). En primer lugar, se desarrolló un nuevo modelo de cadena de valor para la industria eólica. En segundo lugar, identificamos los factores sociales, económicos y ambientales, que influyen significativamente en la competitividad y el desarrollo de la industria eólica a través de un examen claro y preciso de las fortalezas, debilidades, oportunidades y amenazas en la perspectiva del sur de Asia. Se identificaron y analizaron un total de 19 factores. Los resultados de la investigación indican la situación actual y las proyecciones futuras de la industria eólica en un entorno competitivo. Finalmente, sugerimos medidas políticas esenciales para estabilizar el crecimiento de la industria eólica. Este estudio servirá como punto de referencia para el desarrollo constante de la industria de la energía eólica y hacia un sur de Asia seguro y sostenible. Au cours de la dernière décennie, les principaux pays d'Asie du Sud (Pakistan, Inde et Bangladesh) ont efficacement utilisé l'électricité éolienne pour éviter de futures difficultés énergétiques. Cependant, l'industrie éolienne est influencée par un large éventail de facteurs. L'objectif de cette étude est de développer un modèle de chaîne de valeur pour l'industrie éolienne sud-asiatique, d'examiner les facteurs internes et externes pour analyser la viabilité de l'état actuel et de la feuille de route future pour favoriser le secteur de l'énergie éolienne en adoptant le modèle SWOT (Strengths, Weakness, Opportunities, and Threats). Tout d'abord, un nouveau modèle de chaîne de valeur a été développé pour l'industrie éolienne. Deuxièmement, nous avons identifié les facteurs sociaux, économiques et environnementaux, influençant de manière significative la compétitivité et le développement de l'industrie éolienne grâce à un examen clair et précis des forces, des faiblesses, des opportunités et des menaces dans la perspective sud-asiatique. Un total de 19 facteurs ont été identifiés et analysés. Les résultats de la recherche indiquent la situation actuelle et les projections futures de l'industrie éolienne dans un environnement concurrentiel. Enfin, nous avons suggéré des mesures politiques essentielles pour stabiliser la croissance de l'industrie éolienne. Cette étude servira de référence pour le développement constant de l'industrie éolienne et vers une Asie du Sud sûre et durable. During the last decade, the major South Asian countries (Pakistan, India, and Bangladesh) have effectively utilized wind electricity to avoid future energy predicament. However, the wind industry is being influenced by a diverse range of factors. The aim of this study is to develop a value chain model for the South Asian wind power industry, scrutinize both internal and external factors to analyze the viability of present condition and future roadmap to foster the wind energy sector by adopting Strengths, Weakness, Opportunities, and Threats (SWOT) model. Firstly, a novel value chain model was developed for the wind industry. Secondly, we identified the social, economic, and environmental factors, significantly influencing the competitiveness and development of the wind industry through clear and precise examination of strengths, weaknesses, opportunities, and threats in the South Asian perspective. A total of 19 factors were identified and analyzed. Research findings indicate the current situation and future projections of the wind industry in a competitive environment. Finally, we suggested essential policy measures to stabilize the wind industry's growth. This study will serve as a benchmark for the steady development of the wind power industry and towards a secure and sustainable South Asia. خلال العقد الماضي، استخدمت دول جنوب آسيا الرئيسية (باكستان والهند وبنغلاديش) بشكل فعال كهرباء الرياح لتجنب مأزق الطاقة في المستقبل. ومع ذلك، تتأثر صناعة الرياح بمجموعة متنوعة من العوامل. الهدف من هذه الدراسة هو تطوير نموذج سلسلة القيمة لصناعة طاقة الرياح في جنوب آسيا، والتدقيق في كل من العوامل الداخلية والخارجية لتحليل جدوى الوضع الحالي وخارطة الطريق المستقبلية لتعزيز قطاع طاقة الرياح من خلال اعتماد نموذج نقاط القوة والضعف والفرص والتهديدات (SWOT). أولاً، تم تطوير نموذج سلسلة قيمة جديد لصناعة الرياح. ثانيًا، حددنا العوامل الاجتماعية والاقتصادية والبيئية، التي تؤثر بشكل كبير على القدرة التنافسية وتطوير صناعة الرياح من خلال فحص واضح ودقيق لنقاط القوة والضعف والفرص والتهديدات من منظور جنوب آسيا. تم تحديد وتحليل ما مجموعه 19 عاملاً. تشير نتائج البحث إلى الوضع الحالي والتوقعات المستقبلية لصناعة الرياح في بيئة تنافسية. وأخيرًا، اقترحنا تدابير سياسية أساسية لتحقيق الاستقرار في نمو صناعة الرياح. ستكون هذه الدراسة بمثابة معيار للتطور المطرد لصناعة طاقة الرياح ونحو جنوب آسيا آمنة ومستدامة.

Abstract China has exhibited an active attitude with regard to abating global climate change. To analyze the effect of economy development and urbanization quality on interregional energy transmissions against a backdrop of new-type urbanization, this study integrated MRIO model, complex network method, and spatial autocorrelation analysis to systematically analyze the spatiality and spillover effects of interregional energy connections. The results show that the interregional energy connectivity was spatially dependent whilst urban-rural income ratios and population structures were statistically significant in the national-level spatial econometric analysis. Specifically, a regional-level spatial regression analysis demonstrated that population structure, education level, the energy connectivity of other regions, and the income-expenditure ratios of other regions were four determinants that were significant in eastern, central, and western areas. Structural optimization is a key direction for future energy reduction nationwide. This study shed light on the current spillover effects of energy connective intensity, which is beneficial for making stratified and fair energy reduction policies at the regional level.