Energy and exergy analysis of a PCM-based solar powered winter air conditioning using desiccant wheel during nocturnal

In this paper, heating and humidification of air for space have been carried out by using a phase change material (PCM)-based solar-powered desiccant wheel air conditioning (SPDWAC) in winter. The analysis of the setup has been done at different air flow rates. At low and high air flow rates, system has mean thermal coefficient of performance of 0.121 and 0.172, respectively, and mean exergy efficiency of 0.0787 and 0.0846, respectively. The mean thermal coefficient of performance of the system at high air flow rate (127.23 kg h-1) is 1.42 times the low air flow rate (63.62 kg h-1) and average exergy efficiency of the system at high air flow rate is 1.07 times the low air flow rate. It is observed that with an increase in air flow rate, efficiency of the evacuated tube solar air collector (ETSAC) increases. The average efficiency of the ETSAC at high air flow rate is 15.60%. The maximum average energy efficiency (17.80%) and exergy efficiency (17.08%) of the PCM storage system have been obtained at high air flow rate. The overall performance of the system showed that the use of PCM storage is feasible to run the system in winter during the hours of darkness.     

退耕还林工程驱动下的土地利用变化合理性研究——以云南芒市为例

以滇西南中低山盆谷区的芒市为例,在探讨土地利用变化合理度的概念和内涵并构建土地利用变化合理度的评价指标、测算方法和分级标准体系基础上,定量地分析评价了芒市近8 a来退耕还林工程驱动下各个地类变化的合理度和总体土地利用变化的合理度,为推进山区土地资源的可持续利用和退耕还林工程的科学实施提供基础依据。评价结果表明,全市近8 a所有地类转化的总面积为77 602.80 hm²,转化的合理度(RD值)只有48.98%,属于"中度不合理"级。总体上,芒市近8 a来退耕还林工程驱动下的土地利用变化,既有合理的部分,如部分陡坡耕地的生态退耕、荒山造林和封山育林等,但其不合理性亦非常突出,主要体现在生态退耕地中约96%属于"不该退"的宜耕地。此外,在实施退耕还林工程的同时,却又出现较为突出的毁林开垦现象。这些问题的突出存在,使芒市近8 a土地利用变化的合理性程度很低。     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Hierarchical Bayesian Spatial Models for Multispecies Conservation Planning and Monitoring

Abstract: Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence–absence data derived from regional monitoring programs to develop models with both landscape and site‐level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence–absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad‐scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km² hexagons), can increase the relevance of habitat models to multispecies conservation planning.     

双碱法用于烧结烟气脱硫中再生实验的研究

实验考察了影响双碱法再生过程的主要操作参数,包括搅拌速率、再生时间和pH值变化、反应温度、n(Ca(OH)2)/n(Na2SO3)等。使用XRD验证产物成分,用扫描电镜分析了再生CaSO3的形态。实验结果表明:Na2SO3浓度0.3和0.4 mol/L时,保持搅拌速率500 r/min、再生反应时间1 min、温度50℃能够取得最好的再生效果,一次再生后未反应的Ca(OH)2含量大约是34%;降低n(Ca(OH)2)/n(Na2SO3)能提高Ca(OH)2利用率。实验结果能够给再生系统的工程设计提供一定的指导。     

Adsorptive features of banana (Musa paradisiaca) stalk-based activated carbon for malachite green dye removal

Chemically prepared activated carbon derived from banana stalk (BSAC) was used as an adsorbent to remove malachite green (MG) dye from aqueous solution. BSAC was characterised using thermogravimetric analyser, Brunauer Emmett Teller, Fourier transform infrared spectrometry, scanning electron microscopy, pH_pzc, elemental analysis and Boehm titration. The effectiveness of BSAC in adsorbing MG dye was studied as a function of pH, contact time, temperature, initial dye concentration and repeated desorption–adsorption processes. pH_pzc of BSAC was 4.5 and maximum dye adsorption occurred at pH 8.0. The rate of dye adsorption by BSAC was very fast initially, attaining equilibrium within 120 min following a pseudo-second-order kinetic model. Experimental data were analysed by Langmuir, Freundlich and Dubinin–Raduschevich isotherms. Equilibrium data fitted best into the Langmuir model, with a maximum adsorption capacity of 141.76 mg·g^?1. Δ G ⁰ values were negative, indicating that the process of MG dye adsorption onto BSAC was spontaneous. The positive values of Δ H ⁰ and Δ S ⁰ suggests that the process of dye adsorption was endothermic. The regeneration efficiency of spent BSAC was studied using 0.5 M HCl, and was found to be in the range of 90.22–95.16% after four cycles. This adsorbent was found to be both effective and viable for the removal of MG dye from aqueous solution.     

Strategic regeneration: A policy coupling approach to managing a coastal resort in South Wales

This review paper takes a case study approach to critically discuss how regeneration in the coastal resort of Porthcawl, South Wales has integrated flood defences as part of a strategic spatial planning and integrated policy coupling approach to the redesign of the town's seaside, promenade and harbour quarter. This planned initiative is part of a concerted effort to upgrade the town's waterfront and enable regeneration of a small seaside resort. From a resort cycle perspective, Porthcawl's perceived vulnerability to changing economic fortunes has prompted a master planning approach which is intended to bring together a mixed-use development programme with particular attention to urban design, strategic environmental assessment and public consultation. In different ways, this process has sought to raise public awareness of the issues and risks associated with the town's coastal location and to integrate flood defence aspects within the strategic regeneration plan as part of a greater sensitivity to climatic risks and potential flooding. This paper examines the adaptive capacity of coastal communities and the complex of socio-economic and spatio-temporal perspectives that shape policy developments in the planning, development and proactive management of coastal environments. The paper identifies the need to accommodate a new civic awareness of potential environmental hazards in articulating the public interest and balancing the trade-offs involved.     

焙烧态镁铝铁类水滑石对磷酸根离子的吸附

用共沉淀法制备了镁铝铁三元类水滑石(LDH),在不同温度下对其焙烧4 h,得到焙烧态类水滑石(CLDH).采用XRD、FT-IR对材料进行分析,研究其对水中磷酸根的吸附性能和机制.结果表明,铁的掺杂量过大会破坏类水滑石的层状结构,且随着铁含量的增大,类水滑石对磷酸根的吸附量逐渐减小.当Mg/Al/Fe物质的量之比为2∶0.9∶0.1,在300℃下焙烧时,CLDH吸附磷酸根能力最好,吸附容量约27.03 mg.g-1,为焙烧前的1.32倍.在pH 4—11范围内,在竞争离子存在的条件下,CLDH-0.1-300都能表现出较好的吸附性能,对实际废水中的磷也有较强的吸附能力.CLDH-0.1-300对磷酸根的吸附符合二级反应动力学模型,吸附等温线符合Langmuir等温式.用浓度为0.5 mol.L-1的NaOH溶液可以对吸附磷酸根后的类水滑石CLDH-0.1-300实现解吸再生,"吸附-再生-再吸附"循环3次后吸附容量仍接近初始值的60%.     

液化气脱硫醇装置碱渣减排的探索及实践

为减少碱渣排放量,液化气碱洗脱硫醇装置大都设计有碱液催化氧化再生设施。由于传统碱液氧化再生工艺存在副产物二硫化物与再生碱液分离效果差等技术缺陷,其成为液化气脱硫质量的技术瓶颈。从碱液氧化再生原理、二硫化物分离原理等方面寻找突破口,实现了二硫化物大部分的分离回收,系统碱液可长周期循环用于液化气脱硫醇,液态烃碱渣排量减少80%以上。