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1.
PM2.5浓度时空演化特征分析有助于大气污染的现状和发展认知,但PM2.5浓度监测积累时间较短,且受到排放强度和气象因素的影响,因此可融合全球导航卫星系统(Global Navigation Satellite System,GNSS)天顶可降水量(precipitable water vapor,PWV)、风速和大气污染物构建PM2.5浓度模型。以河北省为例,首先分别开展PM2.5浓度与大气污染物、GNSS PWV及风速的相关性分析;然后将大气污染物、GNSSPWV和风速作为输入,PM2.5浓度作为输出,利用逆传播(back propagation,BP)神经网络分别构建城市PM2.5浓度模型和区域PM2.5浓度模型;最后进行PM2.5浓度模型可靠性检验。将模型预测值与PM2.5浓度实测值比较发现,预测PM2.5浓度等级准确率高,相对误差较低。该模型可用于区域PM2.5浓度时空演化特征分析。  相似文献   

2.
The conservation areas in a plain are affected by the groundwater contamination from intense application of the fertilizers. The vulnerability of groundwater can be tested by using the DRASTIC model for the pollutants. The groundwater susceptibility to pollution in the various areas is mapped through DRASTIC model. However, the effects of pollution types and its characteristics are not considered, as this model is used without any modifications. This technique must be standardized for usage in the various aquifers and specific pollution types. The rates of DRASTIC parameters are corrected to obtain the potential for a more accurate analysis of the vulnerability pollution. The relationships between the parameters are identified with respect to the nitrate concentration in the groundwater by calculating the new rates. The methodology was applied to the selected area situated in the south eastern region of Iran at Kerman plain. Twenty-seven different locations were selected to test and analyse the nitrate concentration in the water from underground wells. The pollution in the aquifer was associated and correlated with the DRASTIC index by using the measured nitrate concentrations. The relationship between the index and the measured pollution in the Kerman plain was determined by applying the Wilcoxon rank-sum nonparametric statistical tests and the rates were calculated. It was found specifically in the agricultural areas that the modified DRASTIC model performed more efficiently than the traditional method for nonpoint source pollution, as indicated by the results. After modifications, the regression coefficients revealed that the relationship between the vulnerability index and the nitrate concentration was 77 %, while it was 37 % before the modifications were used. These statistics show that the modified DRASTIC performed far more efficiently than the original version.  相似文献   

3.
ABSTRACT

The automated classification of ambient air pollutants is an important task in air pollution hazard assessment and life quality research. In the current study, machine learning (ML) algorithms are used to identify the inter-correlation between dominant air pollution index (API) for PM10 percentile values and other major air pollutants in order to detect the vital pollutants’ clusters in ambient monitoring data around the study area. Two air quality stations, CA0016 and CA0054, were selected for this research due to their strategic locations. Non-linear RPart and Tree model of Decision Tree (DT) algorithm within the R programming environment were adopted for classification analysis. The pollutants’ respective significance to PM10 occurrence was evaluated using Random forest (RF) of DT algorithms and K means polar cluster function identified and grouped similar features, and also detected vital clusters in ambient monitoring data around the industrial areas. Results show increase in the number of clusters did not significantly alter results. PM10 generally shows a reduction in trend, especially in SW direction and an overall minimal reduction in the pollutants’ concentration in all directions is observed (less than 1). Fluctuations were observed in the behaviors of CO and NOx during the day while NOx displayed relative stability. Results also show that a direct and positive linear relationship exists between the PM10 (target pollutant) and CO, SO2, which suggests that these pollutants originate from the same sources. A semi-linear relationship is observed between the PM10 and others (O3 and NOx) while humidity shows a negative linearity with PM10. We conclude that most of the major pollutants show a positive trend toward the industrial areas in both stations while tra?c emissions dominate this site (CA0016) for CO and NOx. Potential applications of nuggets of information derived from these results in reducing air pollution and ensuring sustainability within the city are also discussed. Results from this study are expected to provide valuable information to decision makers to implement viable strategies capable of mitigating air pollution effects.  相似文献   

4.
Basic principles of compilation and utilization of a multiscale series of evaluative-forecast maps depicting procedures for mitigating the negative environmental impacts of chemical pollution from pesticides are outlined. The accuracy of forecasts of the natural capacity of ecosystems in agricultural regions to purify themselves of pesticide residues can be checked using maps depicting different aspects of chemical pollution across different natural elements of the landscape. Translated from: Izvestiya Akademii Nauk, seriya geograficheskaya, 1994, No. 3, pp. 137-146.  相似文献   

5.
基于极化相干矩阵的河流水质污染监测初探   总被引:1,自引:0,他引:1  
陈炯  贾海峰  杨健  陈玉荣 《遥感学报》2011,15(5):1065-1078
利用遥感手段监测水质污染具有监测范围广、实时性强的优点。本研究选择中国南方地区水质变化明显的河流区域作为研究对象,利用C波段星载极化合成孔径雷达(极化SAR)卫星RADARSAT-2提供的数据,对基于极化SAR的河流水质污染监测技术进行了初步研究。首先介绍了电磁波的极化现象以及极化SAR的基本原理;其次结合一次同步测量实验,提取河流区域,并对极化SAR数据与水质常见监测指标的监测数据进行对比分析,通过对10个采样点18组数据的分析发现,极化相干矩阵中的T 22元素与部分水质指标(如五日生化需氧量BOD5等)具有较强的相关性,从而反映水质的污染状况;并通过实测数据和最小二乘法,拟合得到了利用[T]矩阵元素反演BOD5的经验公式,拟合系数达到0.82。最后通过对地表散射模型和菲涅尔系数的分析,从理论上探讨了极化相干矩阵中部分元素与水体物理性质存在相关性的原因。初步理论分析和实验数据表明,T 22元素能够反映水体的污染状况。  相似文献   

6.
Assessment of human health impact caused by air pollution is crucial for evaluating environmental hazards. In this paper, concentrations of six air pollutants (PM10, PM2.5, NO2, SO2, O3, and CO) were first derived from satellite observations, and then the overall human health risks in China caused by multiple air pollutants were assessed using an aggregated health risks index. Unlike traditional approach for human health risks assessment, which relied on the in-situ air pollution measurements, the spatial distribution of aggregated human health risks in China were obtained using satellite observations in this research. It was indicated that the remote sensing data have advantages over in-situ data in accessing human health impact caused by air pollution.  相似文献   

7.
This study uses space imagery, particularly false-color composites, to identify and map major natural complexes of the Yerevan basin and the changes they are undergoing as a result of a variety of in situ and “imported” pollution impacts. Interpretation aides in the identification of areas affected by different types of pollution in the basin are identified. Translated by Edward Torrey, Alexandria, VA 22308 from: Izvestiya [Rossiyskoy] Akademii Nauk, seriya geograficheskaya, 1992, No. 1, pp. 112–121.  相似文献   

8.
The authors describe a method of applying the cartographic method of research to the study of air and water pollution. More specifically, the paper outlines a program of mapping air, water, and soil pollution in the Donets Basin, which is an integral part of four different stages in the formulation of an environmental protection plan. Emphasis is placed on the visual interpretation of maps depicting the spatial distribution of physical parameters at pollution sources, of concentrations of particular pollutants over the entire study area, and of their direct and cumulative impacts on the environment. Translated from: Geograflya i prirodnyye resursy, 1986, No. 2, pp. 92–94.  相似文献   

9.
A method is presented whereby soil reflectance on remote sensing imagery is used to estimate the level of soil pollution by oil production operations. This method can be used in lieu of the dangerous and toxic solvents now widely employed, and has the additional advantage of applicability to much larger areas. It is based on the construction of a graph and derivative equations depicting the relationship between the spectral reflectances of soils and the soil hydrocarbon content of sample soil plots. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiyand V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvovedenii i ikh ispol'zovaniye v sel'skom kho-zyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp. 161–165.  相似文献   

10.
The paper presents results of applied medical-geographic mapping work by the Uzbek SSR Academy of Sciences in support of public health studies in Central Asian areas where water supplies are contaminated by runoff from irrigated fields. The final product of the work is a map depicting surface water quality in aggregate terms and according to indices for specific pollutants (for water quality monitoring points), which is described both in terms of its content and methods of data compilation and transformation. Translated by Elliott B. Urdang, Providence, RI 02906 from: Izvestiya vysshikh uchebnykh zavedeniy: Geodeziya i aerofotos “yemka, 1989, No. 2, pp. 166–171.  相似文献   

11.
遥感技术在农业立体污染监测中的应用   总被引:5,自引:0,他引:5  
分析我国农业立体污染的客观现实,探讨遥感技术在农业立体污染监测中的应用。主要分析遥感技术在农区水体污染监测、土壤污染时空动态监测、农作物污染变异监测和农业气体污染监测等方面的应用前景; 提出遥感技术与地理信息系统技术相结合,建立综合农业立体污染空间地理信息管理系统,实现农业立体污染的时空动态模拟分析,为农业立体污染防治决策提供科学依据。  相似文献   

12.
Abstract

Upper Lake is the lifeline of Bhopal City, India for drinking and other water needs. In recent years, environmentalists have expressed their serious concern on deteriorating water quality of this lake. Conventional field sampling methods for monitoring lake water quality lack spatial information about the pollution in the lake. It is desirable to have spatial information about the lake for better management and control. In the present paper the remote sensing data from IRS-1C LISS III have been integrated into a GIS environment to analyse and create a pollution zone map of the Upper Lake.

Spectral reflectance analysis was carried out to find the suitability of wavelengths for determining chlorophyll‐a concentration (chl‐a), suspended solid concentration (SSC) and secchi depth (SD). Empirical models relating spectral reflectance and chl‐a, SSC and SD were developed using least square regression analysis. These models were found valid on unused samples. Chl‐a, SSC and SD distribution maps were generated using proposed models and were incorporated as datalayers in the GIS for further analysis of pollution zones. The spatial information of pollution offered by the pollution zone map could delineate regions of lake having high pollution load. The methodology employed in this work can be used for regular monitoring of the pollution in surface water bodies and serve the data needs for better management of the water quality.  相似文献   

13.
通过1:8000彩色红外航片解译,将白银市工业“三废”划分为三大类、十二亚类,编制出大气污染源、固体污染物和污水分布三种专业图件,取得了大量数据,为环保和城建提供了大量有关基础资料。说明航空遥感是调查工矿区工业“三废”的快速、经济、准确的技术方法。  相似文献   

14.
ABSTRACT

Urbanization in China is closely connected with ambient particulate matter 2.5 (PM2.5). However, the potential for altering PM2.5 through the urban landscape characteristics is uncertain. In this study, we analyzed the urban PM2.5 pollution situation for 2014–2016 and investigated the impact of landscape factors on urban PM2.5 in China at the city level. All the prefecture-level cities were stratified by urban population size into small (<500,000), medium (500,000–1,000,000), and large (>1,000,000), and the other second-level administrative cities were assigned as ‘other’ cities. The multivariate regression model including both urban landscape factors and social-economic variables explained 70.0%, 32.8%, 19.2%, and 12.4% of the arithmetic mean PM2.5 concentration (AMC-PM2.5) for the other, small, medium, and large cities, respectively. With regard to the configuration of land cover, agricultural activity is a major contributor of PM2.5 pollution, for which the explanatory power ranged from 7.6% (for the large cities) to 64% (for the other cities). In addition, grassland aggregation also has a limited but negative effect on urban PM2.5 pollution, despite the negligible effect on dry deposition. Overall, these findings likely reflect the interaction between urban air quality and urbanization, and will have implications for air quality control strategies.  相似文献   

15.
Principles are outlined for the use of sub-satellite soil, air, water, and vegetation samples as an auxiliary source of information in remote sensing studies of vegetation stress caused by air pollution. More specifically, procedures for satellite-synchronous aerial overflights, vegetation transects, water quality measurements, and soil tests are described as a basis for delineating boundaries between areas of vegetation stress and unpolluted areas in an industrialized area in the central Urals. Translated from: Kosmicheskiy monitoring biosfery, Yu. A. Izrael', V. V. Bugrovskiy, and Yu. V. Novikov, eds. Leningrad: Gidrometeoizdat, 1985, pp. 93-99.  相似文献   

16.
Materials derived from aerial and space surveys provided the basis for compilation of a series of geomorphological, geological, morphostructural, and lithodynamic maps as well as a map showing sources of manmade pollution. A derivative map of geoecological regions based on these maps makes it possible to estimate qualitatively the ecological state of any coastal region. The Buor-Khaya Gulf of the Laptev Sea is used as a test case. Translated by Edward Torrey, Alexandria, VA 22308 from: Geomorfologiya, 1995, No. 4, pp. 23-34.  相似文献   

17.
《测量评论》2013,45(78):366-368
Abstract

The method of reducing circummeridian altitudes or zenith distances to the meridian, using the factors m and n as tabulated by Chauvenet, is well known. The following method, which does not use these factars, has been faund both more convenient and more accurate in practice. The formula can be easily obtained by expanding m and n in powers of t, but far the sake af campleteness the derivatian is here given from the beginning.  相似文献   

18.
Traditional approaches to monitoring aquatic systems are often limited by the need for data collection which often is time-consuming, expensive and non-continuous. The aim of the study was to map the spatio-temporal chlorophyll-a concentration changes in Malilangwe Reservoir, Zimbabwe as an indicator of phytoplankton biomass and trophic state when the reservoir was full (year 2000) and at its lowest capacity (year 2011), using readily available Landsat multispectral images. Medium-spatial resolution (30 m) Landsat multispectral Thematic Mapper TM 5 and ETM+ images for May to December 1999–2000 and 2010–2011 were used to derive chlorophyll-a concentrations. In situ measured chlorophyll-a and total suspended solids (TSS) concentrations for 2011 were employed to validate the Landsat chlorophyll-a and TSS estimates. The study results indicate that Landsat-derived chlorophyll-a and TSS estimates were comparable with field measurements. There was a considerable wet vs. dry season differences in total chlorophyll-a concentration, Secchi disc depth, TSS and turbidity within the reservoir. Using Permutational multivariate analyses of variance (PERMANOVA) analysis, there were significant differences (p < 0.0001) for chlorophyll-a concentration among sites, months and years whereas TSS was significant during the study months (p < 0.05). A strong positive significant correlation among both predicted TSS vs. chlorophyll-a and measured vs. predicted chlorophyll-a and TSS concentrations as well as an inverse relationship between reservoir chlorophyll-a concentrations and water level were found (p < 0.001 in all cases). In conclusion, total chlorophyll-a concentration in Malilangwe Reservoir was successfully derived from Landsat remote sensing data suggesting that the Landsat sensor is suitable for real-time monitoring over relatively short timescales and for small reservoirs. Satellite data can allow for surveying of chlorophyll-a concentration in aquatic ecosystems, thus, providing invaluable data in data scarce (limited on site ground measurements) environments.  相似文献   

19.
ABSTRACT

Rapid economic growth, a high degree of urbanization and the proximity of a large number of desert and semidesert landscapes can have a significant impact on the atmosphere of adjacent territories, leading to high levels of atmospheric pollution. Therefore, identifying possible sources of atmospheric pollution is one of the main tasks. In this study, we carried out an analysis of spatial and temporal characteristics of five main atmospheric pollutants (PM2.5, PM10, SO2, NO2, and CO) near potential source of natural aerosols, affecting seven cities (Wuhai, Alashan, Wuzhong, Zhongwei, Wuwei, Jinchang, Zhangye), located in immediate proximity to the South Gobi deserts. The results, obtained for the period from 1 January 2016 to 31 December 2018, demonstrate total concentrations of PM2.5 and PM10 are 38.2 ± 19.5 and 101 ± 80.7 μg/m3 exceeding the same established by the Chinese National Ambient Air Quality Standard (CNAAQS), being 35 and 70 μg/m3, respectively. Based on the data from Moderate Resolution Imaging Spectroradiometer (MODIS) for the whole period, Clean Сontinental (71.49%) and Mixed (22.29%) types of aerosols prevail in the region. In the spring and winter seasons maximum concentrations of pollutants and high values of Aerosol Optical Depth (AOD) in the region atmosphere are observed. PM2.5 and PM10 ratio shows the presence of coarse aerosols in the total content with value 0.43. The highest concentrations of pollutants were in the period of dust storms activity, when PM2.5 and PM10 content exceeded 200 and 1000 µg/m3, and AOD value exceeded 1. UV Aerosol Index (UVAI), Aerosol Absorbing Optical Depth (AAOD), and Single Scattering Albedo (SSA), obtained from Ozone Monitoring Instrument (OMI), demonstrate the high content of dust aerosols in the period of sandstorms. Analysis of backward trajectories shows that dust air masses moved from North to Northwest China, affecting large deserts such as Taklamakan, Gurbantunggut, Badain Jaran, Tengger, and Ulan Buh deserts.  相似文献   

20.
The concept that river drainage basins can be considered appropriate spatial units in assessment of human environmental impacts is examined. Applications of remote sensing imagery in the study of changes occurring within a particular basin—the Sit' River in European Russia—are investigated and multispectral aerial photography is used to determine the structure of biotic communities. Regionalization and areal cataloguing of these communities are the basis for specific conclusions regarding the principal sources of entry of nutrients and pollutants into the basin. Three image feature classification methods used to identify such communities (K-means (unsupervised) based on principal components analysis, supervised using principal components analysis, and data compression and subsequent identification of principal components) are compared in terms of effectiveness (numbers of mixed and/or unclassified pixels). Translated by Edward Torrey, Alexandria, VA 22308 from: Izvestiya Akademii Nauk, seriya geograficheskaya, 1994, No. 1, pp. 126-140.  相似文献   

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