Research article Special Issues

Spatial assessment of sewage discharge with urbanization in 2004–2014, Beijing, China

  • Received: 30 August 2016 Accepted: 21 November 2016 Published: 28 November 2016
  • Beijing, China’s cultural political, and economic center, is facing critical water pollution-related challenges warranting global attention. This study used remote sensing and geographic information systems to analyze the impact of urbanization on wastewater discharge in Beijing. Two influencing factors—urban index and environment index—were created from remote sensing image classifications to better reflect the impacts from urbanization and green-cover changes on wastewater discharge. The impacts of urban land uses on the volume of wastewater discharge were examined in localized areas (i.e., the so-called unit watersheds delineated from topography and stream segments). Geostatistical results showed that urbanization was primarily responsible for spatial variations of wastewater discharge. While vegetation helped ameliorate the pollution, increased urban areas on the outskirts of the city resulted in accelerated wastewater discharge. Analytical findings of this study could provide spatially explicit information for policy-makers to initiate and adjust protocols and strategies for protecting water resources and controlling wastewater emission, thus improving quality of living environments in Beijing.

    Citation: Huixuan Li, Cuizhen Wang, Yuqin Jiang, Andrew Hug, Yingru Li. Spatial assessment of sewage discharge with urbanization in 2004–2014, Beijing, China[J]. AIMS Environmental Science, 2016, 3(4): 842-857. doi: 10.3934/environsci.2016.4.842

    Related Papers:

  • Beijing, China’s cultural political, and economic center, is facing critical water pollution-related challenges warranting global attention. This study used remote sensing and geographic information systems to analyze the impact of urbanization on wastewater discharge in Beijing. Two influencing factors—urban index and environment index—were created from remote sensing image classifications to better reflect the impacts from urbanization and green-cover changes on wastewater discharge. The impacts of urban land uses on the volume of wastewater discharge were examined in localized areas (i.e., the so-called unit watersheds delineated from topography and stream segments). Geostatistical results showed that urbanization was primarily responsible for spatial variations of wastewater discharge. While vegetation helped ameliorate the pollution, increased urban areas on the outskirts of the city resulted in accelerated wastewater discharge. Analytical findings of this study could provide spatially explicit information for policy-makers to initiate and adjust protocols and strategies for protecting water resources and controlling wastewater emission, thus improving quality of living environments in Beijing.


    加载中
    [1] World Resource Institute, 2007. Available from: http://www.wri.org/publication/wri-annualreport-2006–2007 (accessed on 21 April 2015).
    [2] Bao LJ, Maruya KA, Snyder SA, et al. (2012) China’s water pollution by persistent organic pollutants. Environ Pollut 163: 100-108.
    [3] Li H, Li Y, Lee MK, et al. (2015) Spatiotemporal analysis of heavy metal water pollution in transitional China. Sustainability 7: 9067-9087. doi: 10.3390/su7079067
    [4] Li Y, Li H, Liu Z, et al. (2016) Spatial Assessment of Cancer Incidences and the Risks of Industrial Wastewater Emission in China. Sustainability 8: 480. doi: 10.3390/su8050480
    [5] Zhang R, HamerlinckJD, Gloss SP, et al. (1996) Determination of Nonpoint-Source Pollution Using GIS and Numerical Models. J Environ Qual 25: 411-418.
    [6] Ebenstein A (2012) The consequences of industrialization: Envidence from water pollution and digestive cancers in China. Rev Econ Stat 94: 186-201. doi: 10.1162/REST_a_00150
    [7] National Academy of Sciences, 2007. Available from: https://www.koshland-science-museum.org/water/html/en/Treatment/Agricultural-and-Industrial-Pollution-in-China.html.
    [8] Chen S (2015) Beijing drinking water reservoir had lead levels’20 times WHO standard’ for at least three years. Available from: http://www.scmp.com/news/china/article/1839337/beijing-drinking-water-reservoir-found-contain-levels-lead-20-times-who.
    [9] Meng W, Qin Y, Zhang B, et al. (2008) Heavy metal pollution in Tainjin Bohai Bay, China. J Environ Sci 7: 814-819.
    [10] Huang F, Wang X, Lou L, et al. (2010) Spatial Variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques. Water res 44: 1562-1572.
    [11] Jiang J, Wang P, Lung W, et al. (2012) A GIS-based generic real-time risk assessment framework and decision tools for chemical spills in the river basin. J Hazard Mater 227: 280-291.
    [12] Sheng J, Wang X, Gong P, et al. (2012) Heavy metals of the Tibetan top soils. Environ Sci Pollut Res 19: 3362-3370.
    [13] Wang Y, Wang P, Bai Y, et al. (2013) Assessment of surface water quality via multivariate statistical techniques: A case study of the Songhua River Harbin region, China. J Hydro-environ Res 7: 30-40.
    [14] Coskun HG, Gulergun O, Yilmaz L (2006) Monitoring of protected bands of Terkos drinking water reservoir of metropolitan Istanbul near the Black Sea coast using satellite data. Int J Appl Earth Observ Geoinfor 8: 49-60.
    [15] Asadi SS, Vuppala P, Anji Reddy M (2007) Remote Sensing and GIS Techniques for Evalution of Groundwater Quality in Municipal Corporation of Hyderabad (Zone-V), India. Int J Environ Res Public Health 4: 45-52.
    [16] Satapathy DR, Salve PR, Katpatal YB (2009) Spatial distribution of metals in ground/surface waters in the Chandrapur district (Central India) and their plausible sources. Environ Geol 56: 1323-1352.
    [17] Dede OT, Telci IT, Aral MM (2013) The use of water quality index models for the evaluation of surface water quality: a case study for Kirmir Basin, Ankara, Turkey. Water Qual, Expos Health 5: 41-56. doi: 10.1007/s12403-013-0085-3
    [18] Wang M, Webber M, Finlayson B, et al. (2008) Rural industries and water pollution in China. J Environ Manage 86: 648-659.
    [19] Ou Y, Wang X (2008) Identification of critical source areas for non-point source pollution in Miyun reservoir watershed near Beijing, China. Water Sci Technol 58: 2235-2241. doi: 10.2166/wst.2008.831
    [20] Wang X, Wang Y, Li T, et al. (2002) Characteristics of non-point source pollution in the watershed of Miyun Reservoir, Beijing, China. Chinese J Geochem 21: 89-96. doi: 10.1007/BF02838057
    [21] Wang X, Ou Y, Dou P, et al. (2009) Relationship between the variation of water quality in rivers and the characteristics of watershed at Miyun, Beijing, China. Chinese J Geochem 28: 112-118. doi: 10.1007/s11631-009-0112-z
    [22] Zhu X, Ji H, Chen Y, et al. (2013) Assessment and sources of heavy metals in surface sediments of Miyun Reservoir, Beijing. Environ monitor assess 185: 6049-6062. doi: 10.1007/s10661-012-3005-2
    [23] Li Z, Li X, Xu Z (2010) Impacts of water conservancy and soil conservation measures on annual runoff in the Chaohe River Basin during 1961–2005. J GeographSci 20: 947-960.
    [24] Zhao H, Li X, Wang X, et al. (2010) Grain size distribution of road-deposited sediment and its contribution to heavy metal pollution in urban runoff in Beijing, China. J hazard mater 183: 203-210. doi: 10.1016/j.jhazmat.2010.07.012
    [25] Foster JA, McDonald AT (2000) Assessing pollution risks to water supply intakes using geographical information systems (GIS). Environ Model Software 15: 225-234.
    [26] Yang T, Liu J (2012) Health Risk Assessment and Spatial Distribution Characteristic on Heavy Metals Pollution of Haihe River Basin. J Environ Analy Toxicol 2: 152.
    [27] Soil and Water Assessment Tool, SWAT. Available from: http://swat.tamu.edu/
    [28] Zhang J, Mauzerall D, Zhu T, et al. (2010) Environmental health in China: progress towards clean air and safe water. Lanset 375: 1110-1119.
    [29] Liu Q, Xie W, Xia J (2013) Using Semivariogram and Moran’s I Techniques to Evaluate Spatial Distribution of Soil Micronutrients. Commun Soil Sci Plan 44: 1182-1192.
    [30] Lee CC, Chiu YB, Sun CH (2010) The environmental Kuznets curve hypothesis for water pollution: Do regions matter? Energy Policy 38: 12-23.
    [31] Liu J, Zhang X, Tran H, et al. (2011) Heavy metal contamination and risk assessment in water, paddy soil, and rice around an electroplating plant. Environ Sci Pollut Res 18: 1623-1632.
    [32] Zhou F, Guo H, Liu Y, et al. (2007) Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach. J Environ Sci 19: 805-810. doi: 10.1016/S1001-0742(07)60135-1
    [33] Murphy RR, Curriero FC, Ball WP (2009) Comparison of spatial interpolation methods for water quality evaluation in the Chesapeake Bay. J Envirol Engineer 136: 160-171.
    [34] Schwarzenbach RP, Egli T, Hofstetter TB, et al. (2010) Global water pollution and human health. Annu Rev Environ Resour 35: 109-136.
    [35] Alexander RB, Boyer EW, Smith RA, et al. (2007) The role of headwater streams in downstream water quality. JAWRA J Am Water Resour Assoc 43: 41-59. doi: 10.1111/j.1752-1688.2007.00005.x
    [36] Liu Z, Li Y, Li Z (2009) Surface water quality and land use in Wisconsin, USA- a GIS approach. J Integr Environ Sci 6: 69-89.
    [37] Huang W, Liu H, Luan Q, et al. (2008) Detection and prediction of land use change in Beijing based on remote sensing and GIS. The Intern Archi of the Photogram, Rem Sens and Spat Inform Sci 37: 75-82.
    [38] China. ORG. CN. China’s Political system, 2013. Available from: http://www.china.org.cn/english/Political/28842.htm
    [39] Li S (2013) All Five of Beijing’s Major Water Systems Seriously Polluted. Available from: http://www.theepochtimes.com/n3/251030-all-five-of-beijings-major-water-systems-seriously-polluted/.
    [40] United States Geological Survey, 2008. Available online: http://earthexplorer.usgs.gov/
    [41] Yearbook CS, China Statistical Yearbook; Beijing, China, 2015.
    [42] The Central People’s Government of the People’s Republic of China, The People’s Republic Of China Yearbook, 2005. Available from: http://www.gov.cn/test/2005-07/27/content_17403.htm.
    [43] Wang C, Bentivegna DJ, Smeda RJ, et al. (2010) Comparing classification approaches for mapping cut-leaved teasel in highway environments. Photogramm Eng Rem S 76: 567-575. doi: 10.14358/PERS.76.5.567
    [44] Rozenstein O, Karnieli A (2011) Comparison of methods for land-use classification incorporating remote sensing and GIS inputs. Appl Geogr 31: 533-544. doi: 10.1016/j.apgeog.2010.11.006
    [45] Sina News, 2016. Available from: http://news.sina.com.cn/green/roll/2016-08-24/doc-ifxvcsrn9082407.shtml
  • Reader Comments
  • © 2016 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(5457) PDF downloads(1015) Cited by(3)

Article outline

Figures and Tables

Figures(7)  /  Tables(5)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog