The value of urban ecosystem services in New York City: A spatially explicit multicriteria analysis of landscape scale valuation scenarios

Mapping, modeling, and valuing urban ecosystem services are important for integrating the ecosystem services concept in urban planning and decision-making. However, decision-support tools able to consider multiple ecosystem services in the urban setting using complex and heterogeneous data are still in early development. Here, we use New York City (NYC) as a case study to evaluate and analyze how the value of multiple ecosystem services of urban green infrastructure shifts with shifting governance priorities. We first examined the spatial distribution of five ecosystem services – storm water absorption, carbon storage, air pollution removal, local climate regulation, and recreation – to create the first multiple ecosystem services evaluation of all green infrastructure in NYC. Then, combining an urban ecosystem services landscape approach with spatial multicriteria analysis weighting scenarios, we examine the distribution of these ecosystem services in the city. We contrast the current NYC policy preference – which is focused on heavy investment in stormwater absorption – with a valuation approach that also accounts for other ecosystem services. We find substantial differences in the spatial distribution of priority areas for green infrastructure for the valuation scenarios. Among the scenarios we examined for NYC, we find that a scenario in which only stormwater absorption is prioritized leads to the most unevenly distributed ES values. By contrast, we find least variation in ES values where stormwater absorption, local climate regulation, carbon storage, air pollution removal, and recreational potential are all weighted equally.We suggest that green infrastructure planning strategies should include all landscape components that contribute to the production of ecosystem services and consider how planning priority alternatives generate different ecosystem services values.     

Field monitoring of volatile organic compounds using passive air samplers in an industrial city in Japan

Highly portable, sensitive, and selective passive air samplers were used to investigate ambient volatile organic compound (VOC) levels at multiple sampling sites in an industrial city, Fuji, Japan. We determined the spatial distributions of 27 species of VOCs in three campaigns: Mar (cold season), May (warm season), and Nov (mild season) of 2004. In all campaigns, toluene (geometric mean concentration, 14.0microg/m3) was the most abundant VOC, followed by acetaldehyde (4.76microg/m3), and formaldehyde (2.58microg/m3). The spatial distributions for certain VOCs showed characteristic patterns: high concentrations of benzene and formaldehyde were typically found along major roads, whereas high concentrations of toluene and tetrachloroethylene (PCE) were usually found near factories. The spatial distribution of PCE observed was extremely consistent with the diffusion pattern calculated from Pollutant Release and Transfer Register data and meteorological data, indicated that passive air samplers are useful for determining the sources and distributions of ambient VOCs.     

Variability of soil-water quality due to Tsunami-2004 in the coastal belt of Nagapattinam district, Tamilnadu

In this study, the Tsunami-caused deterioration of soil and groundwater quality in the agricultural fields of coastal Nagapattinam district of Tamilnadu state in India is presented by analyzing their salinity and sodicity parameters. To accomplish this, three sets of soil samples up to a depth of 30cm from the land surface were collected for the first six months of the year 2005 from 28 locations and the ground water samples were monitored from seven existing dug wells and hand pumps covering the study region at intervals of 3 months. The EC and pH values of both the soil and ground water samples were estimated and the spatial and temporal variability mappings of these parameters were performed using the geostatistical analysis module of ArcGIS((R)). It was observed that the spherical semivariogram fitted well with the data set of both EC and pH and the generated kriged maps explained the spatial and temporal variability under different ranges of EC and pH values. Further, the recorded EC and pH data of soil and ground water during pre-Tsunami periods were compared with the collected data and generated variability soil maps of EC and pH of the post-Tsunami period. It was revealed from this analysis that the soil quality six months after the Tsunami was nearing the pre-Tsunami scenario (EC< 1.5dSm(-1); pH<8), whereas the quality of ground water remained highly saline and unfit for irrigation and drinking. These observations were compared with the ground scenarios of the study region and possible causes for such changes and the remedial measures for taking up regular agricultural practices are also discussed.     

前车突然切入时驾驶人应激生理特性研究

为研究前车突然切入对驾驶人生理负荷的影响,利用MP150生理监测系统对22名被试进行虚拟驾驶试验。采集记录前车突然切入时被试的生理参数。研究驾驶人心率增长率和心率变异性(HRV)指标与车速、应激距离之间的关系。结果表明:自车速度为100 km/h时,随着前车切入距离从55.6 m减小到27.8 m,被试的平均心率增长率从16.21%增大到23.27%,HRV参数低频(LF)值也呈现下降趋势。前车切入距离一定,随着自车车速从60 km/h增加到120 km/h,被试的平均心率增长率存在显著性差异,平均从13.05%上升到21.85%。差异性检验结果表明,前车切入距离和自车速度发生变化时驾驶人的生理负荷变化趋势一致,但自车速度因素对驾驶人生理负荷的影响程度高于切入距离因素。     

Influence of Riparian Seepage Zones on Nitrate Variability in Two Agricultural Headwater Streams

Riparian seeps have been recognized for their contributions to stream flow in headwater catchments, but there is limited data on how seeps affect stream water quality. The objective of this study was to examine the effect of seeps on the variability of stream NO₃‐N concentrations in FD36 and RS, two agricultural catchments in Pennsylvania. Stream samples were collected at 10‐m intervals over reaches of 550 (FD36) and 490 m (RS) on 21 occasions between April 2009 and January 2012. Semi‐variogram analysis was used to quantify longitudinal patterns in stream NO₃‐N concentration. Seep water was collected at 14 sites in FD36 and 7 in RS, but the number of flowing seeps depended on antecedent conditions. Seep NO₃‐N concentrations were variable (0.1‐29.5 mg/l) and were often greater downslope of cropped fields compared to other land uses. During base flow, longitudinal variability in stream NO₃‐N concentrations increased as the number of flowing seeps increased. The influence of seeps on the variability of stream NO₃‐N concentrations was less during storm flow compared to the variability of base flow NO₃‐N concentrations. However, 24 h after a storm in FD36, an increase in the number of flowing seeps and decreasing streamflow resulted in the greatest longitudinal variability in stream NO₃‐N concentrations recorded. Results indicate seeps are important areas of NO₃‐N delivery to streams where targeted adoption of mitigation measures may substantially improve stream water quality.     

“城郊乡”梯度下土壤Cu、Zn、Pb含量的空间变异特征

为揭示城市化、工业化等人为活动对土壤环境质量的影响,选择能反映上海城郊乡梯度差异的中心城区、城郊结合部和远郊,采用地统计学方法对表层土壤样品Cu、Zn、Pb的空间变异结构和分布特征进行了对比分析。结果表明:城市土壤Pb、Cu、Zn的变异系数范围为0.24~0.62,均属中等变异强度。徐汇区土壤Cu、Pb、Zn符合正态分布,闵行区土壤Cu、Pb和Zn符合对数正态分布,奉贤区土壤Zn呈正态分布,土壤Cu、Pb符合对数正态分布。由中心城区到远郊,城市土壤Cu、Pb、Zn的各项统计特征值和变异系数均有较大差异,存在明显的空间分布差异。半方差函数分析结果表明,徐汇区作为中心城区,土壤Cu、Pb、Zn符合球状模型,土壤Cu、Zn具有强烈的空间相关性,土壤Pb具有明显的空间自相关。奉贤区以农业用地为主,土壤Pb符合线性模型,土壤Cu符合高斯模型,土壤Zn符合指数模型,具有强烈的空间相关性。闵行区地处城郊结合部,土壤Cu、Pb、Zn的半方差拟合模型均为线性模型,表现为纯块金形式,以随机变异为主,空间相关性弱。采用Kriging最优内插法进行无偏估值,绘制了表层土壤重金属含量的空间分布图,中心城区、城郊结合部、郊区土壤重金属的空间分布受城市化、工业化、城市交通等因素的影响,均表现出不同的空间分布规律。     

川中丘陵县域土壤pH空间变异及影响因素分析——以四川仁寿县为例

利用2012年在仁寿县采集的555个表层土样(0~20cm),应用地统计学方法分析了该县域尺度表层土壤pH值的空间变异特征;并采用方差分析和回归分析量化主要影响因素对土壤pH值空间变异的影响程度。结果表明:研究区土壤pH值在4.02~8.14之间,平均为6.80,总体上以中性和碱性土壤为主;变异系数为14.48%,属中等程度的空间变异性。地统计分析表明,研究区土壤pH值变异函数的最佳理论模型为球状模型,具有中等程度的空间自相关性,且空间自相关范围较大。方差分析和回归分析表明,土壤类型、成土母质和土地利用方式是显著影响土壤pH值的主要因素。其中,成土母质和土地利用方式分别能独立解释76.2%和4.8%的土壤pH值空间变异。土壤类型的解释能力与分类级别有关,土类、亚类和土属可分别独立解释41.3%、57.3%和83.7%的土壤pH值空间变异,因而能反映成土过程和母质特性的土属是研究区土壤pH值空间变异的主控因素。研究结果可为川中丘陵县域尺度土壤pH空间变异分析及区域生态环境管理与建设提供有益参考。     

Spatial scaling between leaf area index maps of different resolutions

We developed algorithms for spatial scaling of leaf area index (LAI) using sub-pixel information. The study area is located near Liping County, Guizhou Province, in China. Methods for LAI spatial scaling were investigated on LAI images with 960 m resolution derived in two ways. LAI from distributed calculation (LAID) was derived using Landsat ETM+ data (30 m), and LAI from lumped calculation (LAIL) was obtained from the coarse (960 m) resolution data derived through resampling the ETM+ data. We found that lumped calculations can be considerably biased compared to the distributed (ETM+) case, suggesting that global and regional LAI maps can be biased if surface heterogeneity within the mapping resolution is ignored. Based on these results, we developed algorithms for removing the biases in lumped LAI maps using sub-pixel land cover-type information, and applied these to correct one coarse resolution LAI product which greatly improved its accuracy.     

Using GIS to Generate Spatially Balanced Random Survey Designs for Natural Resource Applications

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.     

中国旅游业绿色发展效率时空演变特征及影响机理

绿色发展是旅游业可持续发展理念的重要组成部分,是旅游业奉行以人为本、生态至上和全面发展的新价值观。在梳理旅游业绿色发展概念及内涵基础上,构建旅游业绿色发展效率评价体系,运用SBM-Undersirable模型、核密度估计、空间马尔科夫链等方法,探讨2008—2018年中国31个省（市、自治区）旅游业绿色发展效率（TGDE）时空演化特征及影响机理。研究发现：（1）时间和空间变化方面,TGDE总体处于中等偏下水平,时间上呈“W”型变化形态,“下降—上升—调整”阶段特征显著;空间呈“东—中—西”递减分布,内部差异为西部地区>东部地区>中部地区,低、中、高效率由“金字塔”向“菱形”结构转变,高效率地区集中于东部沿海,中等效率多分布于中西部地区,低效率位于胡焕庸线两侧。（2）动态演进方面,TGDE始终存在两极分化现象,但区域协调性逐步增强,具有较强平稳性,难以实现跨越式发展,空间向上转移省份比较集中,以中西部为主,向下调整省份较少,且存在明显的空间溢出效应,溢出影响具有不对称性。（3）影响机理方面,总体上,经济水平、产业结构、政府规制、教育水平和旅游资源影响因子与TGDE间存在显著的正向关系,对外开放程度的作用不显著,但各因子的影响程度、作用机理及条件具有较强地域性。