Multiple criteria data envelopment analysis for full ranking units associated to environment impact assessment

Zhao, Ming; Cheng, Chun Tian; Chau, Kwok Wing; Li, Gang

doi:10.1504/ijep.2006.011222

Cited by 136 publications

(49 citation statements)

References 19 publications

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“…Although the mathematic expression of precipitation was mentioned a lot in this study, the analysis method was slightly old compared with the latest studies, especially the new methods in machine learning and neural networks [35][36][37][38][39][40], which should be strengthened in follow-up studies. The mechanism of ANPP response to precipitation fluctuation should be revealed more clearly in further studies.…”

Section: Discussionmentioning

confidence: 95%

Impact of Precipitation Fluctuation on Desert-Grassland ANPP

et al. 2016

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Precipitation change has significantly influenced annual net primary productivity (ANPP) at either annual or seasonal scales in desert steppes in arid and semi-arid regions. In order to reveal the process of precipitation driving ANPP at different time scales, responses of different ANPP levels to the inter-annual and intra-annual precipitation fluctuations were analyzed. ANPP was reversed by building a ground reflectance spectrum model, from 2000 to 2015, using the normalized differential vegetation index of the Moderate-Resolution Imaging Spectroradiometer (MODIS-NDVI) data at 250 m × 250 m spatial resolution. Since the description of the differently expressing forms of precipitation are not sufficient in former studies in order to overcome the deficiency of former studies, in this study, intra-annual precipitation fluctuations were analyzed not only with precipitation of May-August, June-August, July-August, and August, respectively, which have direct influence on vegetation productivity within the year, but quantitative description, vector precipitation (R), concentration ratio (Cd), and concentration period (D), were also used to describe the overall characteristics of intra-annual precipitation fluctuations. The concentration ratio and the maximum precipitation period of the intra-annual precipitation were represented by using monthly precipitation. The results showed that: (1) in the period from 1971 to 2015, the maximum annual precipitation is 3.76 times that of the minimum in the Urat desert steppe; (2) vector precipitation is more significantly related to ANPP (r = 0.7724, p = 0.000) compared to meteorological annual precipitation and real annual precipitation influence; and (3) annual precipitation is almost concentrated in 5-8 months and monthly precipitation accumulation has significantly effected ANPP, especially in the period of June-August, since the vegetation composition in the study area was mainly sub-shrubs and perennial grasses, which were more sensitive to precipitation accumulation. These findings suggest that: (1) In the desert steppe, the inter-annual fluctuation and the intra-annual distribution of precipitation have a direct impact on ANPP; (2) the annual vector precipitation showed an extremely significant regression relationship with ANPP; and (3) monthly precipitation fluctuations (May-August) possess the accumulative effect on ANPP during the growing period in the desert steppe, while precipitation accumulation from June to August shows the most significant impact.

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Section: Discussionmentioning

confidence: 95%

Impact of Precipitation Fluctuation on Desert-Grassland ANPP

et al. 2016

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“…There have also been some recent studies using real-life case studies on sustainability elsewhere [16][17][18][19][20][21]. However, these previous studies are generally limited to a small region or to a prefecture, focused on a single or a few chemical elements.…”

Section: Introductionmentioning

confidence: 99%

Distribution and Potential Health Risks of Arsenic, Selenium, and Fluorine in Natural Waters in Tibet, China

Tian

Zha

et al. 2016

Water

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Abstract:The contents of major and trace elements were analyzed in 204 different types of water samples in 138 villages across 51 counties and cities of Tibet. The average concentrations of arsenic (As), selenium, and fluorine for each water category decreased in the following order: arsenic (in µg/L: hot spring 241.37 > lake 27.46 > stream 22.11 > shallow well 11.57 > deep well 6. .52, 2.10, 1.68, and 1.51 µg/L in the prefectures of Shigatse, Nagchu, Lhasa, Lhoka, and Nyingchi, respectively. Carbonatite is a major source of elements in these waters. The non-carcinogenic risk in Tibet caused by heavy metals in drinking water is low overall, except in Ali prefecture's surface and shallow ground waters, which contain high levels of As. Thus, deep well water in Tibet is safe to drink.

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“…The statistical analysis also demonstrated that both socioeconomic transitions and physical environmental conditions are crucial determinants of shaping China's pollution and health maps. In particular, the double-edged effects of industrialization and urbanization reflected the multifactorial processes through which China's development and transitions fundamentally influenced human health with the degradation of the natural environment [34,40,59,72,73].…”

Section: Discussionmentioning

confidence: 99%

Spatial Assessment of Cancer Incidences and the Risks of Industrial Wastewater Emission in China

Liu

et al. 2016

Sustainability

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China's rapid economic growth and social transitions have deteriorated environmental conditions and caused further public health issues in last three decades. This study examines the complex mechanisms of how socioeconomic transitions and physical environmental conditions impact public health, especially with respect to increasing cancer incidences in mainland China from a spatial-temporal perspective. Specifically, (1) spatial variations of seven types of cancer incidences were analyzed in relation to heavy metal emissions from industrial wastewater at the prefecture-level city scale from 2004 to 2009. Additionally; (2) spatial statistical methods were employed to explore the associations between health outcome, heavy metal emissions from industrial wastewater (arsenic, chromium, cadmium, mercury, lead), as well as socioeconomic transitions (industrialization, urbanization, globalization) and physical environmental factors (hydrology and vegetation coverage). Results showed a significant increase of cancer incidences between 2004 and 2009. Consistent with the spatial pattern of heavy metal emissions, cancer patient clusters were identified in both traditional industrial bases and newly industrialized economic zones, especially in major cities located at downstream watersheds, including Beijing, Shanghai, Guangzhou, Shenyang, and Wuhan. The results also revealed the double-edged effects of industrialization, economic growth, and urbanization on natural environment and human health. The findings provide informative knowledge of heavy metal pollution and cancer outbreaks in China and therefore offer valuable reference for authorities formulating regulations.

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Multiple criteria data envelopment analysis for full ranking units associated to environment impact assessment

Cited by 136 publications

References 19 publications

Impact of Precipitation Fluctuation on Desert-Grassland ANPP

Impact of Precipitation Fluctuation on Desert-Grassland ANPP

Distribution and Potential Health Risks of Arsenic, Selenium, and Fluorine in Natural Waters in Tibet, China

Spatial Assessment of Cancer Incidences and the Risks of Industrial Wastewater Emission in China

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