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Journal articles on the topic 'Ecological risk assessment Philippines'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Rubio, C. J., I. S. Yu, H. Y. Kim, and S. M. Jeong. "Index-based flood risk assessment for Metro Manila." Water Supply 20, no. 3 (January 23, 2020): 851–59. http://dx.doi.org/10.2166/ws.2020.010.

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Abstract This study focuses on index-based flood risk assessment in Metro Manila, the capital region of the Philippines and most densely populated region in the country. Its objective is to properly address urban characteristics in flood risk assessment by introducing a specific urban-type set of physical, social, economic and ecological indicators. Analytical hierarchy process (AHP) was used to quantify the optimal selection weights for each of the selected 14 indicators. Five levels of flood risk will be presented in spatial maps using geographic information system (GIS) ranging from Very Low Risk to Very High Risk. Results of this study are expected to aid in understanding flood hazard and risk in Metro Manila. Moreover, the resulting flood risk information can be used as a decision tool in policy making, land-use planning, developing guidelines and countermeasures and flood disaster insurance.

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2

Apdohan, A. G., R. P. Varela, and R. M. Balanay. "CLIMATE RISK VULNERABILITY ASSESSMENT OF THE MAJOR CROPS IN THE PROVINCE OF AGUSAN DEL NORTE, PHILIPPINES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W6-2021 (November 18, 2021): 27–33. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w6-2021-27-2021.

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Abstract. Assessing an area's vulnerability can serve as an effective planning tool to increase resilience to climate-related hazards. This paper provides information on the most vulnerable municipalities to climate change impacts in the province of Agusan del Norte, Philippines. The assessment included in the geospatial analysis were physical, agro-ecological, and socio-economic indicators clustered under the components of exposure, sensitivity, and adaptive capacity. Using MaxEnt, modelling the suitability of crops due to changes in temperature and precipitation by the year 2050 determines the crops' sensitivity. A combination of natural hazards datasets was used to estimate the extent of exposure to each municipality within the province under pressure from climate and hydro-meteorological risks. An up-to-date database from the concerned local government units for adaptive capacity indicators was clustered into seven capitals: economic, natural, human, physical, social, anticipatory, and institutional. The total CRV model for rice, corn, and banana crops revealed that the municipalities identified as highly vulnerable due to their high exposure to climate hazards, the decreasing crops' suitability to climate variability, and low adaptive capacity.

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3

Yap, Chee Kong, and Khalid Awadh Al-Mutairi. "Ecological-Health Risk Assessments of Heavy Metals (Cu, Pb, and Zn) in Aquatic Sediments from the ASEAN-5 Emerging Developing Countries: A Review and Synthesis." Biology 11, no. 1 (December 21, 2021): 7. http://dx.doi.org/10.3390/biology11010007.

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The ASEAN-5 countries (Malaysia, Indonesia, Thailand, Philippines, and Vietnam) of the Association of Southeast Asian Nations as a group is an ever-increasing major economy developmental hub in Asia besides having wealthy natural resources. However, heavy metal (HM) pollution in the region is of increasing environmental and public concern. This study aimed to review and compile the concentrations of Cu, Pb, and Zn in the aquatic sediments of the ASEAN-5 countries published in the literature from 1981 to February 2021. The mean values of Cu, Pb, and Zn in aquatic sediments were elevated and localized in high human activity sites and compared to the earth’s upper continental crust and reference values. Based on 176 reports from 113 publications, the ranges of concentrations (mg/kg dry weight) were 0.09–3080 for Cu, 0.37–4950 for Zn, and 0.07–2666 for Pb. The ecological risk (ER) values ranged from 0.02–1077 for Cu, 0.01–95.2 for Zn, and 0.02–784 for Pb. All reports (100%) showed the Zn ER values were categorized as being between ‘low potential ecological risk’ and ‘considerable potential ecological risk’. Almost all Cu ER values (97.7%) also showed similar ranges of the above two risk categories except for a few reports. The highest Cu level (3080 mg/kg dry weight) was reported from a mine-tailing spill in Marinduque Island of the Philippines with ‘very high ecological risk’. In addition, drainage sediments in the western part of Peninsular Malaysia were categorized as Cu ’high potential ecological risk’. Almost all reports (96%) showed Pb ER values categorized as between ‘low potential ecological risk’ and ‘moderate potential ecological risk’ except for a few reports. Six reports showed Pb ER values of ‘considerable potential ecological risk’, while one report from Semarang (Indonesia) showed Pb ER of ‘very high ecological risk’ (Pb level of 2666 mg/kg dry weight). For the ingestion and dermal contact pathways for sediments from the ASEAN-5 countries, all non-carcinogenic risk (NCR) values (HI values 1.0) for Cu, Pb, and Zn reflected no NCR. The ER and human health risk assessment of Cu, Pb, and Zn were compared in an integrative and accurate manner after we reassessed the HM data mentioned in the literature. The synthesis carried out in this review provided the basis for us to consider Cu, Pb, and Zn as being of localized elevated levels. This provided evidence for the ASEAN-5 group of countries to be considered as being a new socio-economic corridor. Beyond any reasonable doubt, an ever-increasing anthropogenic input of HMs is to be expected to a certain degree. We believe that this paper provides the most fundamental useful baseline data for the future management and sustainable development of the aquatic ecosystems in the region. Lastly, we claim that this review is currently the most up-to-date review on this topic in the literature.

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4

Malone, John, Robert Bergquist, Laura Rinaldi, and Zhou Xiao-nong. "SCHISTOSOMIASIS: GEOSPATIAL SURVEILLANCE AND RESPONSE SYSTEMS IN SOUTHEAST ASIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (October 14, 2016): 1409–11. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1409-2016.

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Geographic information system (GIS) and remote sensing (RS) from Earth-observing satellites offer opportunities for rapid assessment of areas endemic for vector-borne diseases including estimates of populations at risk and guidance to intervention strategies. This presentation deals with GIS and RS applications for the control of schistosomiasis in China and the Philippines. It includes large-scale risk mapping including identification of suitable habitats for <i>Oncomelania hupensis</i>, the intermediate host snail of <i>Schistosoma japonicum</i>. Predictions of infection risk are discussed with reference to ecological transformations and the potential impact of climate change and the potential for long-term temperature increases in the North as well as the impact on rivers, lakes and water resource developments. Potential integration of geospatial mapping and modeling in schistosomiasis surveillance and response systems in Asia within Global Earth Observation System of Systems (GEOSS) guidelines in the health societal benefit area is discussed.

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5

Senoro, Delia B., Cris Edward F. Monjardin, Eddie G. Fetalvero, Zidrick Ed C. Benjamin, Alejandro Felipe B. Gorospe, Kevin Lawrence M. de de Jesus, Mark Lawrence G. Ical, and Jonathan P. Wong. "Quantitative Assessment and Spatial Analysis of Metals and Metalloids in Soil Using the Geo-Accumulation Index in the Capital Town of Romblon Province, Philippines." Toxics 10, no. 11 (October 22, 2022): 633. http://dx.doi.org/10.3390/toxics10110633.

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The municipality of Romblon in the Philippines is an island known for its marble industry. The subsurface of the Philippines is known for its limestone. The production of marble into slab, tiles, and novelty items requires heavy equipment to cut rocks and boulders. The finishing of marble requires polishing to smoothen the surface. During the manufacturing process, massive amounts of particulates and slurry are produced, and with a lack of technology and human expertise, the environment can be adversely affected. Hence, this study assessed and monitored the environmental conditions in the municipality of Romblon, particularly the soils and sediments, which were affected due to uncontrolled discharges and particulates deposition. A total of fifty-six soil and twenty-three sediment samples were collected and used to estimate the metal and metalloid (MM) concentrations in the whole area using a neural network-particle swarm optimization inverse distance weighting model (NN-PSO). There were nine MMs; e.g., As, Cr, Ni, Pb, Cu, Ba, Mn, Zn and Fe, with significant concentrations detected in the area in both soils and sediments. The geo-accumulation index was computed to assess the level of contamination in the area, and only the soil exhibited contamination with zinc, while others were still on a safe level. Nemerow’s pollution index (NPI) was calculated for the samples collected, and soil was evaluated and seen to have a light pollution level, while sediment was considered as “clean”. Furthermore, the single ecological risk (Er) index for both soil and sediment samples was considered to be a low pollution risk because all values of Er were less than 40.

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6

Dominguez, Jacqueline C., Maria Clarissa O. del Moral, Jeshya Obeso A. Chio, Ma Fe P. de Guzman, Boots P. Natividad, Jay-Pee M. Decena, Maryanne Jenelle Y. Montalvo, Macario Reandelar, and Kieu T. T. Phung. "Improving Cognition through Dance in Older Filipinos with Mild Cognitive Impairment." Current Alzheimer Research 15, no. 12 (September 28, 2018): 1136–41. http://dx.doi.org/10.2174/1567205015666180801112428.

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Background: People with mild cognitive impairment (MCI) are considered a high-risk population for developing dementia and therefore potential targets for preventive interventions. So far, no pharmacological interventions have proven to be effective. Latest evidence has laid the groundwork for the hypothesis that dancing can have beneficial effect on cognition by improving neuroplasticity. Objective: This study aimed to examine whether a structured modular ballroom dance intervention (INDAK) could improve cognition among Filipino older persons with MCI. Methods: A two-armed, single-blinded, quasi-experimental study was conducted in a community-based population at Marikina City, Philippines. Two hundred and seven participants older than 60 years old with MCI participated through self-assigned allocation to dance (N=101) and control (N=106) groups. The intervention group received INDAK consisting eight types of ballroom dances with increasing complexity lasting one hour, twice a week for 48 weeks. Neurologists and psychologists blinded to the group allocation administered baseline and post intervention assessments using Alzheimer’s Disease Assessment Scale – Cognitive (ADAS-Cog), Filipino version of the Montreal Cognitive Assessment (MoCA-P), Boston Naming Test (BNT), Geriatric Depression Scale (GDS), Instrumental Activities of Daily Living (IADL) and Disability Assessment for Dementia (DAD). Results: Baseline sociodemographic and clinical characteristics did not differ between groups. The mean differences between baseline and 48-week assessments were compared between dancers and controls, showing that the intervention group improved in ADAS-Cog, MoCA-P, BNT and GDS. Conclusion: INDAK is potentially a novel, ecological and inexpensive non-pharmacological intervention that can improve cognition among older Filipinos with MCI.

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7

Calinawan, Amstrong, Concepcion S. Mendoza, and Leonila Adarna. "Preliminary Study on Deltamethrin Residues in Cabbage, Soil and Water from Dalaguete, Cebu, Philippines." KIMIKA 27, no. 1 (May 25, 2016): 1–11. http://dx.doi.org/10.26534/kimika.v27i1.1-11.

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Pesticides pose a threat to the environment and eventually human health. Extent of contamination of pesticides can be determined and monitored by analysis of pesticide residue in surface water, sediments, soil, and biota. Samples were collected from Manlapay, Barangay Mantalongon in Dalaguete, reportedly the vegetable basket of Cebu, from October to November 2013. Concentration of the pesticide deltamethrin was determined by Gas Chromatography-Electron Capture Detector along with organic matter content (OM), potassium (K) and cation exchange capacity (CEC) using standard methods of analysis. Data showed that deltamethrin was found to be present in soil and cabbage and beyond detection limit in water. Inverse relationship was found between residue in cabbage and in soil confirming pesticide leaching as supported by rainfall data. Organic matter and cation exchange capacity in soil showed significant correlation to detected deltamethrin residue confirming that pyrethroids are strongly bound to organic matter and free exchangeable potassium ions. Deltamethrin residue in water does not show any correlation to any other parameters as it is beyond detection limit, probably due to volatilization and photodegradation of deltamethrin in water. Temperature variation does not show significant difference to deltamethrin residue in all three matrices. The detected deltamethrin residue concentrations in the cabbage (<0.001-0.029 ppm), soil samples (0.007-0.008 ppm) and water samples (<0.0005 ppm) were all below international guideline limits (ASEAN maximum level of 0.5 ppm deltamethrin in cabbage, EC ecologically accepted concentration of 1290 mg deltamethrin/kg soil, and a maximum limit of 0.0025 ppm deltamethrin according to Canadian water quality, respectively). Inspite of the low concentrations detected in cabbage, soil and water samples, an extensive pesticide monitoring on environmental samples within the area is advisable. This will help the adoption of an efficient risk assessment strategy to inform appropriate interventions.

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8

Cura, Jerome. "Ecological risk assessment." Water Environment Research 70, no. 4 (June 1998): 968–71. http://dx.doi.org/10.2175/106143098x134596.

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9

Ziegel, Eric R., and Glenn Suter. "Ecological Risk Assessment." Technometrics 37, no. 2 (May 1995): 240. http://dx.doi.org/10.2307/1269643.

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10

Kangas, Mike. "Ecological Risk Assessment 101." Frontiers in Ecology and the Environment 1, no. 1 (February 2003): 52. http://dx.doi.org/10.1890/1540-9295(2003)001[0052:era]2.0.co;2.

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11

Tannenbaum, Lawrence V. "Detoxifying Ecological Risk Assessment." Human and Ecological Risk Assessment: An International Journal 11, no. 2 (April 2005): 469–72. http://dx.doi.org/10.1080/10807030590927658.

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12

Fargašová, Agáta. "Ecological Risk Assessment Framework." Acta Environmentalica Universitatis Comenianae 24, no. 1 (March 1, 2016): 10–16. http://dx.doi.org/10.1515/aeuc-2016-0002.

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AbstractPurpose of this paper is to draft shot information about framework for ecological risk assessment compile according Guidelines and short description of phases from which this method consists. During description of particular procedures, the meaning of used terms is introduced and explained. The framework for risk assessment is presented as a useful tool for risk management and selection of available cleanup and remedy technologies, and costs of alternative actions.

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13

Cura, Jerome J. "Ecological and health risk assessment." Water Environment Research 69, no. 4 (June 1997): 925–30. http://dx.doi.org/10.2175/106143097x135136.

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14

Funke, Odelia C. "Limitations of ecological risk assessment." Human and Ecological Risk Assessment: An International Journal 1, no. 4 (October 1995): 443–53. http://dx.doi.org/10.1080/10807039509380029.

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15

Solomon, Keith R., and John P. Giesy. "ECOLOGICAL RISK ASSESSMENT OF PESTICIDES." Human and Ecological Risk Assessment: An International Journal 7, no. 3 (May 2001): 493–95. http://dx.doi.org/10.1080/20018091094501.

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16

Menzie, Charles A., and Jonathan S. Freshman. "An assessment of the risk assessment paradigm for ecological risk assessment." Human and Ecological Risk Assessment: An International Journal 3, no. 5 (November 1997): 853–92. http://dx.doi.org/10.1080/10807039709383732.

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17

Renner, Rebecca. "Ecological Risk Assessment Struggles to Define Itself: Ecological Risk Case Study." Environmental Science & Technology 30, no. 4 (March 1996): 174A. http://dx.doi.org/10.1021/es962724z.

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18

Principe, Peter P. "Ecological benefits assessment: A policy‐oriented alternative to regional ecological risk assessment." Human and Ecological Risk Assessment: An International Journal 1, no. 4 (October 1995): 423–35. http://dx.doi.org/10.1080/10807039509380027.

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19

Suter, Glenn W. "Ecological Risk Assessment and Ecological Epidemiology for Contaminated Sites." Human and Ecological Risk Assessment: An International Journal 12, no. 1 (February 2006): 31–38. http://dx.doi.org/10.1080/10807030500428553.

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20

Gibbs, Mark. "Ecological Risk Assessment, Prediction, and Assessing Risk Predictions." Risk Analysis 31, no. 11 (March 30, 2011): 1784–88. http://dx.doi.org/10.1111/j.1539-6924.2011.01605.x.

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21

Biksey, Thomas M., Amy Couch Schultz, and William Phillips. "Ecological and Human Health Risk Assessment." Water Environment Research 73, no. 6 (October 1, 2001): 1699–730. http://dx.doi.org/10.2175/106143001x144546.

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22

Biksey, Thomas M., Amy Couch Schultz, William H. Phillips, Amy M. Romano, and Elisa D. Gross. "Ecological and Human Health Risk Assessment." Water Environment Research 74, no. 6 (October 1, 2002): 1633–67. http://dx.doi.org/10.2175/106143002x144798.

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23

Biksey, Thomas M., Amy Couch Schultz, and Aaron M. Bernhardt. "Ecological and Human Health Risk Assessment." Water Environment Research 75, no. 6 (October 1, 2003): 1879–949. http://dx.doi.org/10.2175/106143003x145390.

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24

Biksey, Thomas M., Amy Couch Schultz, and Aaron M. Bernhardt. "Ecological and Human Health Risk Assessment." Water Environment Research 76, no. 6 (September 2004): 2510–67. http://dx.doi.org/10.2175/106143004x145894.

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Biksey, Thomas M., Amy Couch Schultz, and Aaron M. Bernhardt. "Ecological and Human Health Risk Assessment." Water Environment Research 77, no. 6 (September 2005): 2835–901. http://dx.doi.org/10.2175/106143005x54687.

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26

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, and Brett Marion. "Ecological and Human Health Risk Assessment." Water Environment Research 78, no. 10 (September 2006): 2097–98. http://dx.doi.org/10.2175/106143006x119521.

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27

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, Preston Smith, Brett Marion, and Chrissy Isbister. "Ecological and Human Health Risk Assessment." Water Environment Research 79, no. 10 (September 2007): 2170–91. http://dx.doi.org/10.2175/106143007x218700.

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28

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, Preston Smith, Brett Marion, and Chrissy Isbister. "Ecological and Human Health Risk Assessment." Water Environment Research 80, no. 10 (October 2008): 1997–2025. http://dx.doi.org/10.2175/106143008x328888.

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29

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, Brett Marion, and Chrissy Isbister. "Ecological and Human Health Risk Assessment." Water Environment Research 81, no. 10 (September 10, 2009): 2170–210. http://dx.doi.org/10.2175/106143009x12445568400818.

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30

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, Brett Marion, and Chrissy Peterson. "Ecological and Human Health Risk Assessment." Water Environment Research 82, no. 10 (January 1, 2010): 2067–94. http://dx.doi.org/10.2175/106143010x12756668802256.

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31

Biksey, Thomas M., Amy Couch Schultz, Aaron M. Bernhardt, Brett Marion, Chrissy Peterson, and Preston Smith. "Ecological and Human Health Risk Assessment." Water Environment Research 83, no. 10 (January 1, 2011): 1876–905. http://dx.doi.org/10.2175/106143011x13075599870252.

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32

Biksey, Tom, Amy Couch Schultz, Aaron Bernhardt, Chrissy Peterson, and Kelly Taylor. "Ecological and Human Health Risk Assessment." Water Environment Research 84, no. 10 (October 1, 2012): 1856–77. http://dx.doi.org/10.2175/106143012x13407275695797.

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33

Dale, Virginia H., Gregory R. Biddinger, Michael C. Newman, James T. Oris, Glenn W. Suter, Timothy Thompson, Thomas M. Armitage, et al. "Enhancing the Ecological Risk Assessment Process." Integrated Environmental Assessment and Management 4, no. 3 (2008): 306. http://dx.doi.org/10.1897/ieam_2007-066.1.

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34

Cheryl Hogue. "Sunscreen chemicals need ecological risk assessment." C&EN Global Enterprise 100, no. 28 (August 15, 2022): 19. http://dx.doi.org/10.1021/cen-10028-polcon4.

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35

Charabi, Yassine, B. S. Choudri, and Mushtaque Ahmed. "Ecological and Human Health Risk Assessment." Water Environment Research 90, no. 10 (October 1, 2018): 1777–91. http://dx.doi.org/10.2175/106143018x15289915807434.

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36

Andow, David A., Gábor L. Lövei, and Salvatore Arpaia. "Ecological risk assessment for Bt crops." Nature Biotechnology 24, no. 7 (July 1, 2006): 749–51. http://dx.doi.org/10.1038/nbt0706-749.

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37

Rand, G. M. "Commentary: hormesis and ecological risk assessment." Human & Experimental Toxicology 20, no. 10 (October 2001): 525–26. http://dx.doi.org/10.1191/096032701718120391.

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38

Fox, David R. "Statistical Issues in Ecological Risk Assessment." Human and Ecological Risk Assessment: An International Journal 12, no. 1 (February 2006): 120–29. http://dx.doi.org/10.1080/10807030500430476.

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39

Merrell, Paul. "Legal issues of ecological risk assessment." Human and Ecological Risk Assessment: An International Journal 1, no. 4 (October 1995): 454–58. http://dx.doi.org/10.1080/10807039509380030.

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40

Power, Michael. "Probability concepts in ecological risk assessment." Human and Ecological Risk Assessment: An International Journal 2, no. 4 (December 1996): 650–54. http://dx.doi.org/10.1080/10807039609383643.

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41

Weeks, J. M., and S. D. W. Comber. "Ecological risk assessment of contaminated soil." Mineralogical Magazine 69, no. 5 (October 2005): 601–13. http://dx.doi.org/10.1180/0026461056950274.

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AbstractThe basis for an ecological risk assessment based on meeting the needs of recent UK and EU legislation is described. The background to the framework and the legislative driver and relevant definitions of harm are provided, prior to an overview of the proposed ecological risk assessment process, which has been broken down into a Tiered approach. Tier 0 requires the establishment of a conceptual site model, where potential contaminant-pathway-receptor linkages are sought and, assuming they are identified, lead on to higher Tier assessments. Tier 1 relies largely on chemical analysis of soil contaminant levels and comparison with soil quality guideline values to assess the likelihood of harm. In some cases biological screening assays may also be undertaken within this Tier. Based on a weight of evidence approach, should data from Tier 1 indicate harm or leave uncertainty, then Tier 2 biological testing is undertaken using assays relevant to the site of interest. In situations where harm is identified under Tier 2 then Tier 3 is reserved for establishing the extent of harm within the ecosystem. Finally the use of the 'weight-of-evidence' approach to generate scientifically robust conclusions regarding the harm (or potential for harm) within the ecosystem is briefly outlined. The framework discussed is currently being adopted by the UK Environment Agency, with implementation expected in 2005. The UK scheme compares favourably with comparative schemes operating in other countries possessing the merits of being iterative, tiered, flexible with agreed exit points subject to satisfying defined criteria and so speeding the decision-making process.

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42

HOPPER, B. E. "Ecological aspects of pest risk assessment." EPPO Bulletin 21, no. 3 (September 1991): 587–94. http://dx.doi.org/10.1111/j.1365-2338.1991.tb01292.x.

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43

Hutchinson, T. H., R. Brown, K. E. Brugger, P. M. Campbell, M. Holt, R. Länge, P. McCahon, L. J. Tattersfield, and R. van Egmond. "Ecological risk assessment of endocrine disruptors." Environmental Health Perspectives 108, no. 11 (November 2000): 1007–14. http://dx.doi.org/10.1289/ehp.001081007.

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44

Ragas, A. "Ecological risk assessment of chemical mixtures." Toxicology Letters 295 (October 2018): S37. http://dx.doi.org/10.1016/j.toxlet.2018.06.1154.

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45

Bai, Junhong, Laibin Huang, Haifeng Gao, and Guangliang Zhang. "Wetland biogeochemistry and ecological risk assessment." Physics and Chemistry of the Earth, Parts A/B/C 97 (February 2017): 1–2. http://dx.doi.org/10.1016/j.pce.2017.02.004.

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46

Chénier, Robert. "An Ecological Risk Assessment of Formaldehyde." Human and Ecological Risk Assessment: An International Journal 9, no. 2 (March 2003): 483–509. http://dx.doi.org/10.1080/713609919.

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47

Taylor, Ken W., Pierre-Yves Caux, and Dwayne R. J. Moore. "An Ecological Risk Assessment of Hexachlorobutadiene." Human and Ecological Risk Assessment: An International Journal 9, no. 2 (March 2003): 511–25. http://dx.doi.org/10.1080/713609920.

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48

Jóźwiak, Zofia, and Marta Barańska. "Ecological Risk Assessment of Ballast Water." Procedia - Social and Behavioral Sciences 151 (October 2014): 122–26. http://dx.doi.org/10.1016/j.sbspro.2014.10.013.

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49

Chapman, Peter M. "Ecological risk assessment (ERA) and hormesis." Science of The Total Environment 288, no. 1-2 (April 2002): 131–40. http://dx.doi.org/10.1016/s0048-9697(01)01120-2.

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50

Wang, Haowei, Lichen Zhu, Chunyuan Zhao, and Shuanning Zheng. "Urban ecological risk assessment management platform." International Journal of Sustainable Development & World Ecology 25, no. 5 (January 19, 2018): 477–82. http://dx.doi.org/10.1080/13504509.2018.1425934.

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