Optimal spatial resolution for collection of ground data and multi-sensor image mapping of a soil erosion cover factor

Military training activities disturb ground and vegetation cover of landscapes and increases potential soil erosion. To monitor the dynamics of soil erosion, there is an important need for an optimal sampling design in which determining the optimal spatial resolutions in terms of size of sample plots used for the collection of ground data and the size of pixels for mapping. Given a sample size, an optimal spatial resolution should be cost-efficient in both sampling costs and map accuracy. This study presents a spatial variability-based method for that purpose and compared it with the traditional methods in a study area in which a soil erosion cover factor was sampled and mapped with multiple plot sizes and multi-sensor images. The results showed that the optimal spatial resolutions obtained using the spatial variability-based method were 12 and 20m for years 1999 and 2000, respectively, and were consistent with those using the traditional methods. Moreover, the most appropriate spatial resolutions using the high-resolution images were also consistent with those using ground sample data, which provides a potential to use the high-resolution images instead of ground data to determine the optimal spatial resolutions before sampling. The most appropriate spatial resolutions above were then verified in terms of cost-efficiency which was defined as the product of sampling cost and map error using ordinary kriging without images and sequential Gaussian co-simulation with images to generate maps.     

Application of spatial multi-criteria analysis to site selection for a local park: a case study in the Bergamo Province, Italy

This contribution discusses a site selection process for establishing a local park. It was supported by a value-focused approach and spatial multi-criteria evaluation techniques. A first set of spatial criteria was used to design a number of potential sites. Next, a new set of spatial and non-spatial criteria was employed, including the social functions and the financial costs, together with the degree of suitability for the park to evaluate the potential sites and to recommend the most acceptable one. The whole process was facilitated by a new software tool that supports spatial multiple criteria evaluation, or SMCE. The application of this tool, combined with a continual feedback by the public administration, has provided an effective methodology to solve complex decisional problem in land-use and urban planning.     

Spatial Analysis of Soil Salinity and Soil Structural Stability in a Semiarid Region of New South Wales,Australia

Salt-affected soils are a major threat to agriculture especially in the semiarid regions of the world. The effective management of these soils requires adequate understanding of not only how water and, hence, solutes are transported within the soil, but also how soil salinity and sodicity spatially interact to determine soil structural breakdown. For sustainable agricultural production, information on quantitative soil quality, such as salinity, is required for effective land management and environmental planning. In this study, quantitative methods for mapping indicators of soil structural stability, namely salinity and sodicity, were developed to assess the effect of these primary indicators on soil structural breakdown. The current levels of soil salinity, as measured by electrical conductivity (EC) of the soil/water suspension, soil sodicity, represented by exchangeable sodium percentage (ESP), and aggregate stability, were assessed. Remote sensing, geographical information system (GIS), and geostatistical techniques-primarily regression-kriging and indicator-kriging-were used to spatially predict the soil sodicity and salinity. The patterns of salinity (EC) and sodicity (ESP > 5%) were identified. The effect of land use on these soil quality indicators was found to be minimal. Co-spatial patterns were elucidated between sodic soils (defined by ESP > 5%) and highly probable mechanically dispersive soils predicted from indicator-kriging of ASWAT scores. It was established that the incorporation of EC with ESP into an objective index, called electrolyte stability index (ESI = ESP/EC), gave a good indication of soil dispersion, although the threshold ESI value below which effective structural breakdown might occur is 0.025, which is twice as small as the expected 0.05. The discrepancies between ESI and ASWAT scores suggest that other soil factors than salinity and sodicity are affecting soil structural breakdown. This calls for further investigation. The study provides valuable information in the form of risk zones of soil structural breakdown for land management. These zones, with a probability of mechanical soil dispersion of >0.70, require immediate management attention with greater monitoring and amelioration techniques, particularly gypsum or lime application and/or altered cultivation techniques.     

Evolution of road risk disparities at small-scale level: example of Belgium

PROBLEM: Road accident outcomes are traditionally analyzed at state or road network level due to a lack of aggregated data and suitable analytical methods. The aim of this paper is to demonstrate usefulness of a simple spatiotemporal modeling of road accident outcomes at small-scale geographical level. METHOD: Small-area spatiotemporal Bayesian models commonly used in epidemiological studies reveal the existence of spatial correlation in accident data and provide a mechanism to quantify its effect. The models were run for Belgium data for the period 2000-2005. Two different scale levels and two different exposure variables were considered under Bayesian hierarchical models of annual accident and fatal injury counts. The use of the conditional autoregressive (CAR) formulation of area specific relative risk and trend terms leads to more distinctive patterns of risk and its evolution. The Pearson correlation tests for relative risk rates and temporal trends allows researchers to determine the development of risk disparities in time. RESULTS: Analysis of spatial effects allowed the identification of clusters with similar risk outcomes pointing toward spatial structure in road accident outcomes and their background mechanisms. From the analysis of temporal trends, different developments in road accident and fatality rates in the three federated regions of Belgium came into light. Increasing spatial disparities in terms of fatal injury risk and decreasing spatial disparities in terms of accident risk with time were further identified. IMPACT ON INDUSTRY: The application of a space-time model to accident and fatal injury counts at a small-scale level in Belgium allowed identification of several areas with outstandingly high accident (injury) records. This could allow more efficient redistribution of resources and more efficient road safety management in Belgium.     

Influence of input uncertainty on prediction of within-field pesticide leaching risks

Previous research has suggested that pesticide losses at the field scale can be dominated by a small proportion of the field area. The objective of this study was to investigate whether site-specific applications (i.e. avoiding high-risk areas) at the field scale can contribute to a reduction of pesticide leaching despite uncertainty in the underlying model-based leaching risk map. Using a meta-model of the dual-permeability model MACRO, the annual average pesticide leaching concentrations were estimated for 162 sample sites on a 47 ha field. The procedure was repeated for different scenarios describing different patterns of spatial variation of degradation half-lives and the partition coefficient to soil organic carbon. To account for interpolation uncertainty, maps of predicted pesticide leaching risk were produced by the method of sequential Gaussian simulation. The results of the case study show that larger reductions of predicted leaching were achieved by site-specific application than by that of a comparable uniform dose reduction. Hence, site-specific-applications may be a feasible method to reduce pesticide leaching at the field-scale providing that the model approach gives reasonable estimates of the spatial pattern of pesticide leaching.     

Geographical and pedological drivers of distribution and risks to soil fauna of seven metals (Cd, Cu, Cr, Ni, Pb, V and Zn) in British soils

Concentrations of seven metals were measured in over 1000 samples as part of an integrated survey. Sixteen metal pairs were significantly positively correlated. Cluster analysis identified two clusters. Metals from the largest (Cr, Cu, Ni, V, Zn), but not the smallest (Cd, Pb) cluster were significantly negatively correlated with spatial location and soil pH and organic matter content. Cd and Pb were not correlated with these parameters, due possibly to the masking effect of recent extensive release. Analysis of trends with soil properties in different habitats indicated that general trends may not necessarily be applicable to all areas. A risk assessment indicated that Zn poses the most widespread direct risk to soil fauna and Cd the least. Any risks associated with high metal concentrations are, however, likely to be greatest in habitats such as arable and horticultural, improved grassland and built up areas where soil metal concentrations are more frequently elevated.     

邻里效应对牧户载畜率决策的影响——北方牧区的经验证据

草畜平衡管理已经在中国实施近20年,但天然草原超载过牧问题尚未得到根本解决,仍然是制约北方草原生态恢复和畜牧业健康发展的关键因素。如何进一步降低牧户载畜率,实现草畜平衡是亟待解决的问题。该研究基于社会经济学视角,理论分析了牧户载畜率决策邻里效应的存在性及其对牧户载畜率的影响效应、作用机制及异质性,并利用2020年在内蒙古、甘肃两省牧区对820户牧户的微观调查数据,采用线性均值模型、中介效应模型和分组回归等方法进行了实证检验。结果表明:(1)牧户载畜率决策存在邻里效应,表现出"近墨者黑"特征,且这一效应在控制内生性后依旧存在;牧户会受邻里高载畜率、高超载过牧比例的消极驱动呈现出高载畜率和高超载过牧概率,从而陷入超载过牧的恶性循环。(2)机制分析表明,邻里效应通过提高牧户畜牧业预期收益和降低牧户的心理负担提升牧户载畜率。(3)调节作用分析表明,邻里效应会受到榜样群体的调节,村干部、党员、富人和能人等榜样群体的负向示范强化了载畜率决策的邻里效应,抑制牧户降低载畜率。(4)异质性分析表明,邻里效应在低载畜率、贫困牧户、汉族牧户和受教育程度高的牧户群体中作用更小;当政府外部生态监管严格和村域内部非正式制度健全时,邻里效应对牧户降低载畜率的抑制作用更小。根据以上结论,建议政府在微观草畜平衡管理中,通过打造高效畜牧业样板、树立生态典型、强化舆论压力、改善生态监管和注重政策瞄准等方式,破解载畜率决策邻里效应的负面影响,降低牧户载畜率。     

工业园区和城区VOCs组成及化学活性的空间差异对清远大气臭氧污染分布的影响

工业化与城镇化交替演进使珠三角及其周边地区土地利用类型较为复杂。快速的城市化进程使城市建成区与大量村镇工业园区互相交错。这种变化势必会增加挥发性有机物(VOCs)在组分构成和空间分布上的复杂性,并对臭氧(O₃)污染的时空变化产生影响。为厘清这种排放的空间异质性特征及其对O₃污染分布的影响,分别选取可以代表清远市典型工业园区和城市建成区的站点开展观测研究。结果表明:工业园区和城市建成区VOCs浓度水平和污染特征有较大的空间差异,其中代表村镇工业园区的龙塘站VOCs日均浓度为30.42×10^-9,高于代表城市建成区的技师学院站(17.32×10^-9)。龙塘站二甲苯和甲苯的臭氧生成潜势(OFP)比技师学院站高57.6×10^-9,且该值相当于技师学院站排名前10位物种OFP的总和。气象分析表明:2个站点之间并非彼此的上、下风向,而是共同受到局地气团的影响。源解析结果表明:源排放是造成这种空间异质性的内因,其中交通源对技师学院的贡献更高,而工业相关排放源对龙塘的贡献更高。该研究进一步比较了周边站点O₃时间序列的一致性,并模拟2个站点的O₃生成速率。研究发现O₃在局地范围内变化较小,高VOCs排放的地点对局地O₃有较高的贡献,局地内不同地点的O₃生成过程也存在较大差异。据此,笔者提出O₃污染防控建议:短期内可通过技术手段和观测数据发现O₃污染的重要贡献点,并进行针对性的"散乱污"清理整治和涉VOCs行业综合整治,长期看应科学合理规划城市发展布局和产业布局,预留城市通风廊道,以有效减少O₃污染。     

长江经济带环境规制对工业绿色转型的影响研究

本文立足长江经济带环境规制与工业绿色转型实践，分析了双重市场激励型规制影响工业绿色转型的内在机理，并利用2002—2017年长江经济带11个省市面板数据进行实证分析。研究发现：①双重市场激励型规制均显著地促进了工业绿色转型，但是费用型规制的促进效应存在递减特征。②异质性检验表明，费用型规制对长江中下游地区、人均GDP较高省份以及第二产业占比较高省份的工业绿色转型促进效应更为明显。③中介效应模型检验结果显示，提高末端治理技术是工业绿色转型的重要渠道。④研究还发现，费用型规制对高能耗行业、二氧化硫排放量和粉尘排放量具有显著的抑制效应，投资型规制对废水排放量和固体废物排放量的抑制效应更明显。⑤随着工业绿色转型程度的不断提升，双重市场激励型规制对工业绿色转型的边际效应先后呈现“ L”形骤降特征。因此不断优化与创新环境规制手段，才是持续推进工业绿色转型的关键所在。     

济南市夏季甲醛时空分布特征及对臭氧污染的影响

基于Sentinel-5P卫星遥感数据,分析济南市2019—2021年夏季甲醛浓度的时空分布特征及对臭氧污染的影响。结果表明：研究期间夏季甲醛平均柱浓度呈逐年下降趋势,2020年同比降幅最大为24%;甲醛浓度高值区域主要分布在人口密集的市区及工业聚集的章丘区、济阳区和商河县,呈现由城市中心向外扩散的趋势;甲醛浓度受周边城市的影响,形成一条东西向的区域化污染带;甲醛对臭氧的影响主要表现在臭氧污染轻度或污染初期,而氮氧化物的排放进一步加重臭氧污染。