Evaluation of the best compromise between the urban air quality monitoring resolution by diffusive sampling and resource requirements

The need to collect data representative of overall urban pollution is all-important in order to monitor the population exposure. High spatial resolution monitoring using diffusive samplers allows studying of the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost. In this study we point out how to find the best compromise between the number of necessary measurements and the affordable costs for monitoring campaigns. We also describe an innovative method for the proper design of a fixed urban monitoring network by means of preliminary high spatial resolution campaigns using diffusive samplers. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO(2) concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km. The statistical processing of data produced a twofold result: the creation of isoconcentration maps with geostatistical procedures, and an algorithm aimed at locating the minimum number of sampling sites where the fixed monitoring stations should be placed. Average urban levels estimated on the basis of these selected sites differ by less than 8% from those calculated on the whole populations of the sampled points. The aim of this work is to investigate how far the resolution of a monitoring campaign of urban pollution by diffusive sampling can be reduced, thus making the monitoring less expensive in terms of human and financial resources, while preserving the same quality of the results that could be achieved with a higher resolution. We found that there is no significant loss of information when the resolution of the monitoring grid for BTEX is lowered to a mesh size of 1.85 km, that is a sampling site each 3.4 km(2), and that the minimum number of sampling sites to be used is N = 0.29 A, where A is the urban surface to be monitored (in km(2)). As the spatial distribution of NO(2) is less sensitive to the distance from the emission source than that of BTEX, this relationship could be retained as a valid lower limit for the mesh grid size also for NO(2) monitoring.     

Transition index maps for urban growth simulation: application of artificial neural networks,weight of evidence and fuzzy multi-criteria evaluation

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.     

A necessary distinction between spatial representativeness of an air quality monitoring station and the delimitation of exceedance areas

The European legislation on ambient air quality introduces the concepts of spatial representativeness of a monitoring station and spatial extent of an exceedance zone. Spatial representativeness is an essential macro-scale siting criterion which should be evaluated before the setting-up and during the life of a monitoring point. As for the exceedance area, it has to be defined each time an environmental objective is exceeded in an assessment zone. No specific approach is prescribed to delimit such areas. A probabilistic methodology is presented, based on a preliminary kriging estimation of atmospheric concentrations at each point of the domain. It is applied to NO₂ pollution on the urban scale. In the proposed approach, a point belongs to the area of representativeness of a station if its concentration differs from the station measurement by less than a given threshold. To take the estimation uncertainty into account, the standard deviation of the kriging error is used in a probabilistic framework. The choice of the criteria used to deal with overlapping areas is first tested on NO₂ annual mean concentration maps of France, built by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. At the local scale, data from passive sampling surveys and high -resolution auxiliary variables are used to provide a more precise estimation of the background pollution in different French cities. The traffic-related pollution can also be accounted for in the map by additional predictors such as distance to the road, and traffic-related NO_x emissions. Similarly, the proposed approach is implemented to identify the points, at a given statistical risk, where the NO₂ concentration is above the annual limit value.     

The monitoring results of electromagnetic radiation of 110-kV high-voltage lines in one urban location in Chongqing P.R. China

To understand electromagnetic radiation field strength and its influencing factors of certain 110-kV high-voltage lines in one urban area of Chongqing by measuring 110-kV high-voltage line’s electromagnetic radiation level. According to the methodology as determined by the National Hygienic Standards, we selected certain adjacent residential buildings, high-voltage lines along a specific street and selected different distances around its vertical projection point as monitoring points. The levels of electromagnetic radiations were measured respectively. In this investigation within the frequency of 5–1,000 Hz both the electric field strength and magnetic field strength of each monitoring sites were lower than the public exposure standards as determined by the International Commission on Non-Ionizing Radiation Protection. However, the electrical field strength on the roof adjacent to the high-voltage lines was significantly higher than that as measured on the other floors in the same buildings (p < 0.05). The electromagnetic radiation measurements of different monitoring points, under the same high-voltage lines, showed the location which is nearer the high-voltage line maintain a consistently higher level of radiation than the more distant locations (p < 0.05). Electromagnetic radiation generated by high-voltage lines decreases proportionally to the distance from the lines. The buildings can to some extent shield (or absorb) the electric fields generated by high-voltage lines nearby. The electromagnetic radiation intensity near high-voltage lines may be mitigated or intensified by the manner in which the high-voltage lines are set up, and it merits attention for the potential impact on human health.     

北京市中心商区射频电磁环境测试与分析

各类无线技术的发展和应用导致公众曝露于环境中的电磁场辐射的程度越来越高,由此引发的对人体健康风险的担忧促使诸多国家和组织开展了相关研究,并制定了电磁环境控制限值,电磁环境的空间分布也成为至关重要的基础数据。于2019年10—12月对北京市中心3个典型商区的电磁环境进行了测试,测试频段为10 MHz～8 GHz,属于射频范围。通过空间插值方法对测试数据进行处理,从而得到测试区域的射频电磁环境空间分布地图。对测试数据的进一步分析表明,测试区域的射频电磁环境水平主要分布在0.5～2.5 V/m,随空间距离变化较为剧烈,总体上符合《电磁环境控制限值》(GB 8702—2014)的要求。建议在城市发展过程中,对射频电磁环境进行持续、精细的监测。     

Patchy distribution fields: sampling distance unit of a zigzag survey and reconstruction adequacy

A mathematical model was used to examine the effects of choosingvarious units of sampling distance of a zigzag survey on the adequacy of reconstructing patchy distribution fields. The modelsimulates fish or plankton patches (or gaps) of different shapesand spatial orientations, and an acoustic survey by zigzag or parallel transects along which a unit of sampling distance is set. Adequacy of the reconstructed fields to those originally generated is evaluated by calculating their correlations (r). A priori information on the autocorrelation radii for the field in the directions of the survey (R_s) and perpendiculardirection (R_p) allows optimisation of the survey design andthe algorithm of data analysis. A field can be reconstructed properly (r² > 0.70) if the distance between transects D < (1.0–1.5)R_s and the unit of sampling distance d < (1.0–1.5)R_p. A posteriori determination of patchorientation allows reconstruction of the best field attainable onthe basis of the survey data. In cases of field movement, if thedimension of patches in the direction of movement exceeds that ofa surveyed area, a survey in the opposite direction gives bestresults; in contrast, if the dimension of moving patches is smaller than that of a surveyed area, it is reasonable to carryout a survey in the same direction. The criterion remains validwhen a survey is carried out by zigzag transects and a unit ofsampling distance is set along them. The results obtained indicate that, for a fixed transect spacing and a given number of sampling points on each full transect, zigzag pattern allowsless adequate reconstruction of an original distribution field (in cases of both immovable and movable fields) than corresponding parallel pattern.     

Monitoring Studies of Augusta Bay Marine Waters

The monitoring of water quality today provides a great quantity of data consisting of the values of the parameters measured as a tunction of bme or as spatial function.In the marine environment, and especially in the suspended material, increasing importance is being given to the presence of particular pollution indices. With the increase in the number of sampling points, the amount of data increases and examining the results and their consequent interpretation becomes more difficult. To overcome such difficulties, numerous chemometric techniques have been introduced in environmental chemistry, such as Principal Component Analysis (PCA).The use of the PCA in this work has been applied to the analysis of twenty three different sampling points in three seasonal sampling cruises in the same year. This led to recognition of the influence and the localisation of wastewaters in the Augusta bay after measuring the water pollution parameters.The PCA made evident the difference between some sampling sites whose data were initially thought to be similar where the presence of hot industrial water discharge or urban wastewater determines the permanent water quality.Furthermore, it has allowed a choice of more significant parameters for monitoring programs and more representative sampling site locations.     

Numerical Model Inter-comparison for Wind Flow and Turbulence Around Single-Block Buildings

Wind flow and turbulence within the urban canopy layer can influence the heating and ventilation of buildings, affecting the health and comfort of pedestrians, commuters and building occupants. In addition, the predictive capability of pollutant dispersion models is heavily dependent on wind flow models. For that reason, well-validated microscale models are needed for the simulation of wind fields within built-up urban microenvironments. To address this need, an inter-comparison study of several such models was carried out within the European research network ATREUS. This work was conducted as part of an evaluation study for microscale numerical models, so they could be further implemented to provide reliable wind fields for building energy simulation and pollutant dispersion codes. Four computational fluid dynamics (CFD) models (CHENSI, MIMO, VADIS and FLUENT) were applied to reduced-scale single-block buildings, for which quality-assured and fully documented experimental data were obtained. Simulated wind and turbulence fields around two surface-mounted cubes of different dimensions and wall roughness were compared against experimental data produced in the wind tunnels of the Meteorological Institute of Hamburg University under different inflow and boundary conditions. The models reproduced reasonably well the general flow patterns around the single-block buildings, although over-predictions of the turbulent kinetic energy were observed near stagnation points in the upwind impingement region. Certain discrepancies between the CFD models were also identified and interpreted. Finally, some general recommendations for CFD model evaluation and use in environmental applications are presented.     

Post-remediation evaluation of a LNAPL site using electrical resistivity imaging

Present understanding of the earth's subsurface is most often derived from samples at discrete points (wells) and interpolations or models that interpret the space between these points. Electrical resistivity imaging techniques have produced an improved capability to map contaminants (especially NAPLs--NonAqueous Phase Liquids) away from traditional wells using actual field data. Electrical resistivity image data, confirmed by drilling, have demonstrated that LNAPL (Light NAPL--less dense than water, such as gasoline) contaminants exist outside of a delineated and remediated area in Golden, Oklahoma. The data also demonstrate that LNAPL exists between monitoring and remediation wells which indicate low contaminant levels when sampled. Additionally, the electrical images provided the drilling location with the highest concentration of hydrocarbon ever found on the site, even after two phases of remediation work had been performed, although the sampling protocols varied. The results indicate that current methods of post-remediation site characterization are inadequate for complete site characterization.     

基于Landsat 8遥感数据的天津市地表温度反演

以Landsat 8遥感数据为数据源,进行天津市地表温度反演研究。首先采用单通道算法反演地表温度,并利用均值标准差法进行温度分级。然后建立不同温度等级面积比例的估算模型。再通过随机样点,从不同温度等级和土地覆盖类型2个角度,分别建立并比较不同类样点的地表温度与各指数的拟合模型。结果表明:次高温区域面积比例与人口密度、人均GDP都具有较高的决定系数;地表温度与NDVI、BAEM的二元线性回归决定系数高于地表温度与单一指数的决定系数;将样点分类后,低温点与MNDBI的决定系数高于其他温度等级样点,水域和植被样点与各种指数的决定系数高于其他地物类型样点。     

Multi-scale Atmospheric Dispersion Modelling by Use of Adaptive Gridding Techniques

An accurate prediction of the transport-reaction behaviour of atmospheric chemical species is required to fully understand the impact on the environment of pollution emissions. Elevated levels of secondary pollutants such as ozone in the lower atmosphere can be harmful to the health of both plants and animals, and can cause damage to property present in the urban environment. Detailed models of pollution mechanisms must therefore be developed through comparisons with field measurements to aid the selection of effective abatement policies. Such models must satisfy accuracy requirements both in terms of the number of species represented, and the spatial resolution of species profiles. Computational expense often compels current models to sacrifice detail in one of these areas. This paper attempts to address the latter point by presenting an atmospheric transport-reaction modelling strategy based upon a finite volume discretisation of the atmospheric dispersion equation. The source terms within this equation are provided by an appropriate reduced chemical scheme modelling the major species in the boundary layer. Reaction and transport discretisations are solved efficiently via a splitting technique applied at the level of the non-linear equations. The solution grid is generated using time dependant adaptive techniques, which provide a finer grid around regions of high spatial error in order to adequately resolve species concentration profiles. The techniques discussed are applied in two dimensions employing emissions from both point and area sources. Preliminary results show that the application of adaptive gridding techniques to atmospheric dynamics modelling can provide more accurately resolved species concentration profiles, accompanied by a reduced CPU time invested in solution. Such a model will provide the basis for high resolution studies of the multiple scale interactions between spatially inhomogeneous source patterns in urban and regional environments.     

Flow Field and Pollution Dispersion in a Central London Street

Urban pollution due to roadways is perceived as a major obstacle to implementing low-energy ventilation design strategies in urban non-domestic buildings. As part of a project to evaluate the use of a computational fluid flow model as an environmental design tool for urban buildings, this paper seeks to address the impact of pollution from roadways on buildings in areas of restricted topography and assess dominant influencing factors and other requirements for testing the flow model predictions. Vertical profiles of carbon monoxide (CO) and temperature at the facade of a building in a Central London street, in addition to above-roof wind speed and direction, were measured over a period of three months. The street has a height-to-width (h/W) ratio of 0.6 and is of asymmetric horizontal alignment. The air flows in the area surrounding the building were modelled using a computational fluid flow model for two orthogonal wind directions. CO concentrations were calculated from the steady-state flow field in order to place point measurements in the context of the flow field, identify persistent features in the measured data attributable to the flow structure and, by comparison with measurements, identify further testing requirements.Some qualitative and quantitative agreement between measured and modelled data was obtained. Measured CO levels at the building facade and vertical variations of CO were small, as predicted by the model. A wake-interference type flow was predicted by the model for wind speeds >2ms-1 with formation of a vortex cell occurring for roof-level wind speeds >5ms-1 for the cross-wind direction, which was reflected in the measured CO levels and facade gradients. A direction-dependent inverse relationship was noted, both in the model and measurements, between above-roof wind speed and facade CO levels although statistical correlations in the time series were poor. CO concentrations at the facade were found to increase with height frequently, as well as decrease, especially for parallel winds. It is expected that mechanical turbulence due to vehicles was largely responsible. In comparison, thermal stratification appeared to play only a minor role in controlling vertical mixing in the street, under low wind speed conditions.     

Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC’s change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC’s change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC’s change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)–81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC’s changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China’s urban expansion and cropland loss during 1990–2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998–2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.     

The use of δ(15)N signatures of translocated macroalgae to map coastal nutrient plumes: improving species selection and spatial analysis of metropolitan datasets

The definition of the spatial footprint of land-derived nutrient plumes is a key element to the design of initiatives to combat eutrophication in urbanised coastal regions. These plumes, however, are difficult to monitor because of their inherent high-frequency temporal and spatial variability. Biomonitoring with macroalgae provides time-integration of bioavailable nitrogen inputs through the measurement of δ(15)N signatures in tissues, and adequate spatial coverage through translocation to desirable monitoring locations. In this study, we used laboratory incubations to compare three different species of macroalgae as bioindicators, and a field experiment to investigate the applicability of the technique for the large-scale mapping of nutrient plumes. Cladophora valonioides was selected for the field experiment as it showed rapid changes in δ(15)N values in the laboratory incubations, was abundant in shallow depths making collection cost-efficient, and had tough thalli capable of withstanding deployment in open water. Ecklonia radiata also performed well in the laboratory incubations, but field harvest from subtidal depths was comparatively more expensive. Ulva lactuca had fragile thalli, and large nitrogen reserves that acted to mask the isotopic signal of newly acquired nitrogen. Cladophora valonioides was translocated to 246 sites covering an area of ～445 km(2) along the highly urbanized temperate coast of Adelaide, South Australia. The resulting isotopic signatures of nitrogen in tissues were spatially interpolated to produce maps of land-derived nutrient plumes, to model probability and standard error in the predictive surface, and to optimize sampling design.     

Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979�C2009) in China

This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979?C2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.     

Water quality assessment, by statistical analysis, on rural and urban areas of Chocancharava River (Río Cuarto), Córdoba, Argentina

Water quality has degraded dramatically in the Chocancharava River (Río Cuarto, Córdoba, Argentina) due to point and non-point sources. This paper aims to assess spatial and temporal variations of physical and chemical parameters of the river. Six sampling sites and six sampling campaigns were developed. During the period 2007–2008, wet and dry seasons were included. A statistical analysis was carried out with 23 physical and chemical variables. Then, a new statistical analysis was carried out including the Riparian Corridors Quality Index and the physical and chemical variables (24 variables). Considering a multivariate system, analysis of variance, principal component analysis and cluster analysis were used. From the statistical analysis, the river was divided into two zones with different degrees of contamination. The most polluted zone is due to pollution inputs of urban, industrial and agricultural sources. This area showed a remarkable deterioration in water quality, mainly due to wastewater discharges. According to Riparian Quality, better results were found in sections of poor water quality, due to the fact that the river bank forest was less degraded downstream of the sewage discharge.     

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.     

Sampling Scale Effects in Random Fields and Implications for Environmental Monitoring

The concept of a sampling scale triplet of spacing, extent and support is used to define the spatial dimensions of a monitoring network or a field study. The spacing is the average distance between samples, the extent is the size of the domain sampled and the support is the averaging area of one sample. The aim of this paper is to examine what is the bias and the random error (uncertainty) introduced by the sampling scale triplet into estimates of the mean, the spatial variance and the integral scale of a variable in a landscape. The integral scale is a measure of the average distance over which a variable is correlated in space. A large number of two dimensional random fields are generated from which hypothetical samples, conforming to a certain sampling scale triplet, are drawn which in turn are used to estimate the sample mean, spatial variance and integral scale. The results indicate that the biases can be up to two orders of magnitude. The bias of the integral scale is positively related to the magnitude of any of the components of the scale triplet while the bias of the spatial variance is different for different components of the scale triplet. All sampling scale effects are relative to the underlying correlation length of the variable of interest which is closely related to the integral scale. The integral scale can hence be used for sampling design and data interpretation. Suggestions are given on how to adjust a monitoring network to the scales of the variables of interest and how to interpret sampling scale effects in environmental data.     

Spatial pattern analysis in Persian oak (Quercus brantii var. persica) forests on B&W aerial photographs

The purpose of this investigation was to develop a method to determine the spatial pattern of trees as a robust indicator to monitor changes from B&W aerial photographs in Persian oak forests of Zagros, Iran. A 500 x 600 m study area was selected in Servak forests next to Yasuj city in Kohgiluyeh-Va-BuyerAhmad Province. All the trees were tagged in the study area and the point map of stems were prepared. The spatial distribution of trees was determined as "dispersed" using nearest neighbour technique. Then the index of "C" calculated by T-square sampling method was applied to the point map of the study area in 30 systematic sample points in a 100 x 100 m network. Comparing the results of this method with the true spatial pattern of the study area showed that "C" can detect the spatial arrangement of trees. Thereafter the index was used on the air photo of the study area that was made of B&W aerial photographs. The method suggested in this study provides a suitable approach for detecting the spatial pattern of trees in Zagros forests on B&W air photos.     

The Draft of the New German Guideline VDI 3782/8 to Model Automobile Exhaust Dispersion

The draft of the German guideline to calculate automobile exhaust dispersion is explained. It contains a two-stage-system: For first quick estimates the guideline contains the simple models MLuS and STREET. In case these models are not applicable or their results shows concentration levels close to the air quality standards, the more complex models PROKAS_V and MISKAM are recommended. PROKAS_V is a Gaussian plume model, MISKAM is a 3-dimensional microscale non hydrostatic flow model for built-up areas with an Eulerian dispersion model. The guideline comprises cases in rural areas without or with few adjacent buildings as well as urban areas with buildings near the roads. The contribution gives information about the models, typical results and some of the problems showing up presently.