The relationship between centrality and land use patterns: Empirical evidence from five Chinese metropolises

The relationship between location and land use patterns is one of the classic theoretical issues in urban studies. Classic models based on the monocentricity hypothesis have limitations in the interpretation of modern urban structure. China has experienced institutional transformation in recent decades, and the interaction of national government policy, market forces and the natural environment has influenced urban planning in Chinese metropolises, resulting in urban structures with special characteristics. This paper examines the distribution of location and land use intensity, and tested the Alonso model by the relationship between them in five Chinese metropolises using Point of Interest data, space syntax methodology, the grid weighted statistical method and the Geographically Weighted Regression (GWR) model. Universal patterns about the scaling relation between intensity of land use types and the centrality of location are revealed. The elasticity of land use types to location, from high to low sensitivity, is commercial, residential then industrial land in most of the five metropolises studied. The sensitivity sequence of land use studied suggests that the hypothetical model based on the classical Alonso model can explain the spatial structure of modern metropolises in China to some extent, especially for the commercial land. But the order of sensitivity of residential land and industrial land to location does not conform to the model. The spatial heterogeneity in land use intensity and centrality were explored and the factors embedded were discussed. It can be found that the relation between centrality and land use intensity conforms to power law. In most of the metropolises studied, when the scaling relation between land use intensity and centrality is super linear, the sequence of the frequency value from high to low are commercial, residential and industrial land; when the scaling relation is sublinear, the sequence of the frequency value is industrial, residential and commercial land.     

Association of solid fuel use with risk of stunting in children living in China

Stunting adversely affects physical and mental outcomes of children. It has not been examined whether household air pollution from solid fuel combustion is a risk factor for stunting in children. In a total of 41,439 children aged 6-17 across China, height was measured using a unified protocol. Multivariable linear regression models and logistic regression models were used to assess the associations of solid fuel use for cooking/heating with stunting in children. Adjusted for covariates, cooking/heating with solid fuel was significantly associated with a lower z-score for height for age and sex (β = −0.21 [−0.32 to −0.09] and −0.17 [−0.31 to −0.03], respectively) and an increased risk of stunting with an estimated ORs of 1.34 [1.07~1.68] and 1.37 [1.02~1.83], respectively. The risk of stunting associated with solid fuel use was statistically significant in high-age children. And the effect was greater on girls than on boys, though the difference was not statistically significant. Our study suggested that Chinese children living in households using solid fuel had a significantly higher risk of stunting than those living in households using cleaner fuel.     

Machine-learning paradigms for selecting ecologically significant input variables

Harmful algal blooms, which are considered a serious environmental problem nowadays, occur in coastal waters in many parts of the world. They cause acute ecological damage and ensuing economic losses, due to fish kills and shellfish poisoning as well as public health threats posed by toxic blooms. Recently, data-driven models including machine-learning (ML) techniques have been employed to mimic dynamics of algal blooms. One of the most important steps in the application of a ML technique is the selection of significant model input variables. In the present paper, we use two extensively used ML techniques, artificial neural networks (ANN) and genetic programming (GP) for selecting the significant input variables. The efficacy of these techniques is first demonstrated on a test problem with known dependence and then they are applied to a real-world case study of water quality data from Tolo Harbour, Hong Kong. These ML techniques overcome some of the limitations of the currently used techniques for input variable selection, a review of which is also presented. The interpretation of the weights of the trained ANN and the GP evolved equations demonstrate their ability to identify the ecologically significant variables precisely. The significant variables suggested by the ML techniques also indicate chlorophyll-a (Chl-a) itself to be the most significant input in predicting the algal blooms, suggesting an auto-regressive nature or persistence in the algal bloom dynamics, which may be related to the long flushing time in the semi-enclosed coastal waters. The study also confirms the previous understanding that the algal blooms in coastal waters of Hong Kong often occur with a life cycle of the order of 1–2 weeks.     

Comprehensive Benefit Evaluation System for Low-Impact Development of Urban Stormwater Management Measures

In recent years, plenty of simulation research about the low impact development(LID) control effect has emerged, but studies on scheme comparison and evaluation are lacking. In this study, a comprehensive benefit evaluation system for LID, including environmental, economic, and social benefits, was established on the basis of Analytic Hierarchy Process(AHP) and urban storm water model. Above all, benefit identification, quantitative evaluation and scheme comparison of single LID measures were obtained according to site investigation, simulated calculation and theoretical analysis. Whereafter, LID combination plans were designed based on single LID measures with high comprehensive benefit values, and their comprehensive benefits were evaluated to obtain the optimal plan. Then, based on well-founded system combined with Storm Water Management Model (SWMM), the design and optimization of LID were conducted, with a case in Xi’an, China. It turned out that the preferential order of the LID single measures according to the comprehensive benefit was: bio-retention > rain barrels > low-elevation greenbelt > green roofs > permeable pavement. Five LID combination plans were designed based on bio-retention, rain barrels, low-elevation greenbelt, and green roofs. Evaluation results showed that plan I (bio-retention and green roofs) was the optimal LID combination plan.     

陕北无定河流域土壤侵蚀与植被覆盖和降雨关系研究

基于2000—2014年陕北无定河流域日降水、DEM、土壤类型、MODIS NDVI等数据,利用修正通用土壤流失方程(RUSLE)估算了流域土壤侵蚀情况,定量分析了植被覆盖和降雨在土壤侵蚀中的作用,结果表明:(1)无定河流域土壤侵蚀以微度侵蚀为主,平均占流域面积的88.35%,各土壤侵蚀等级面积比例随等级的升高而降低。2000—2014年微度侵蚀面积比例为下降趋势,轻度及以上等级面积比例均为上升趋势。(2)不考虑降雨因子影响时,无定河流域仍以微度侵蚀为主,且为增加趋势,而其他土壤侵蚀等级均为下降趋势。不考虑植被覆盖因子时,流域土壤侵蚀与模型计算结果的变化趋势基本一致。(3)植被覆盖对土壤侵蚀面积比例和变化速率的贡献率分别为13.67%和24.55%,而降雨作用达到86.33%和75.44%,表明降雨是流域土壤侵蚀的主要动力和控制因子,降雨变化主导着流域土壤侵蚀变化过程。     

化学强化生物除磷工艺及设计

本文介绍了一种新的化学强化生物除磷工艺及其设计实例，与Phostrip侧流除磷工艺相比，其工艺优势在于所有污泥均经释磷和厌氧选择处理，通过化学沉积释放的磷，从而消除了在污泥处置过程中产生的磷释放回到污水处理系统的问题；所有回流污泥经厌氧选择处理，含有较高浓度聚磷菌类微生物，从而具有较高的除磷效率。     

Long-term and seasonal nitrate trends illustrate potential prevention of large cyanobacterial biomass by sediment oxidation in Hamilton Harbour,Lake Ontario

Several studies have shown that large, experimental additions of nitrate (NO₃) to eutrophic systems can mitigate large populations of nuisance cyanobacteria and that high NO₃ concentrations can oxidize anoxic sediments. These studies are consistent with observations from numerous aquatic systems across a broad trophic range showing development of reduced surficial sediments precedes the formation of large cyanobacteria populations. We use 50+ years of data to explore whether high NO₃ concentrations may have been instrumental both in the absence of large populations of cyanobacteria in eutrophic Hamilton Harbour, Lake Ontario in the 1970s when total phosphorus (TP) and total nitrogen (TN) concentrations were high, and in delaying large populations until August and September in recent decades despite much lower TP and TN. Our results indicate that large cyanobacteria population events do not occur at the central station in July-September when epilimnetic NO₃ > 2.2 mg N L^?1. The results further suggest that remedial improvements to wastewater treatment plant oxidation capacity may have been inadvertently responsible for high NO₃ concentrations > 2.2 mg N L^?1 and thus for mitigating large cyanobacteria populations. This also implies that large cyanobacteria populations may form earlier in the summer if NO₃ concentrations are lowered.     

周庄旅游客源市场空间结构研究

基于客源市场结构相关理论,结合游客问卷调查数据,系统分析了周庄国内旅游客源市场的人口学特征、空间分布特征和旅游流动模式。研究表明,长三角地区作为核心客源市场对于周庄的持续发展起着非常大的作用。客源市场和地理集中指数都不高,说明游客来源地比较分散,客源市场吸引范围较广。依据客源市场空间结构与客流空间特征,可以将周庄国内客源市场划分为长三角、北京、广东等一级市场,东部沿海与长江中下游"T"字型区域的二级市场以及其他机会市场3个目标层次。     

Removal of hexavalent chromium in aquatic solutions by pomelo peel

This study investigated the removal of hexavalent chromium(Cr(VI)) in aqueous solutions using pomelo peel(PP) and FeCl_3-modified pomelo peel(FPP) as novel biomass adsorbents.Batch adsorption experiments were performed to evaluate the effects of pH,time,temperature,initial concentration,and adsorbent dose on Cr(VI) removal by PP and FPP.The results show that the maximum adsorption capacity of Cr(VI)was 21.55 mg/g for FPP and 0.57 mg/g for PP at a pH of 2.0 and a temperature of 40℃.The surface shape,microstructure,and chemical composition of FPP were analyzed with scanning electron microscopy(SEM),Fourier transform infrared spectroscopy(FTIR),and energy dispersive spectroscopy(EDS),and compared with those of PP.The results show that the adsorption performance of FPP was much better than that of PP,indicating that FPP can be an alternative high-efficiency adsorbent for Cr(VI) removal.     

对我国城市雨水利用误区的思考

城市雨水资源的利用是一个方兴未艾的领域,我国城市雨水资源利用刚刚起步,但已出现了一些问题,并走向了种种误区.在简要分析我国城市雨水利用规划现状的基础上,探讨了现阶段城市雨水利用过程中存在的误区,并针对亟待解决的问题提出了建议.