Jose Castro, Javier Mateo-Sagasta and Saskia Nowicki
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Through a systematic literature review of 49 journal publications, complemented by 15 key informant interviews, this article examines the methods and outputs of CS programs in resource-constrained settings. We explore the potential of these programs to contribute to tracking SDG 6.3.2. Using the CS impact assessment framework, we evaluate broader outcomes of CS programs across 5 domains: society, economy, environment, governance, and science and technology. Despite large variability in scope, CS programs were consistently found to generate useful data for national-level reporting on physicochemical and ecological parameters; however, data quality is a concern for CS measurement of microbiological parameters. The focus in literature to-date is predominantly on scientific data production which falls only within the ‘science and technology’ outcome domain. Societal, governance, economic, and environmental outcomes are infrequently evaluated. Of the studies reviewed in this article, 75% identified some form of pollution but only 22% of them reported follow-up actions such as reporting to authorities. While CS has important potential, work is still needed towards the ‘formalization’ of CS, particularly if intended for more vulnerable contexts.","PeriodicalId":11747,"journal":{"name":"Environmental Research Letters","volume":"41 1","pages":""},"PeriodicalIF":5.8000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancing ambient water quality monitoring and management through citizen science in low- and middle-income countries\",\"authors\":\"Jose Castro, Javier Mateo-Sagasta and Saskia Nowicki\",\"doi\":\"10.1088/1748-9326/ad7305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In contexts where conventional environmental monitoring has historically been limited, citizen science (CS) for monitoring efforts can be an effective approach for decentralized data generation that also raises scientific literacy and environmental awareness. To that end, the United Nations Environmental Program is considering CS as a mechanism for producing ambient water quality data to track progress on sustainable development goal (SDG) indicator 6.3.2: ‘proportion of bodies of water with good ambient water quality’. However, the alignment of SDG 6.3.2 monitoring requirements with CS capacity and results in low- or middle-income countries has not been assessed. Through a systematic literature review of 49 journal publications, complemented by 15 key informant interviews, this article examines the methods and outputs of CS programs in resource-constrained settings. We explore the potential of these programs to contribute to tracking SDG 6.3.2. Using the CS impact assessment framework, we evaluate broader outcomes of CS programs across 5 domains: society, economy, environment, governance, and science and technology. Despite large variability in scope, CS programs were consistently found to generate useful data for national-level reporting on physicochemical and ecological parameters; however, data quality is a concern for CS measurement of microbiological parameters. The focus in literature to-date is predominantly on scientific data production which falls only within the ‘science and technology’ outcome domain. Societal, governance, economic, and environmental outcomes are infrequently evaluated. Of the studies reviewed in this article, 75% identified some form of pollution but only 22% of them reported follow-up actions such as reporting to authorities. While CS has important potential, work is still needed towards the ‘formalization’ of CS, particularly if intended for more vulnerable contexts.\",\"PeriodicalId\":11747,\"journal\":{\"name\":\"Environmental Research Letters\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental Research Letters\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1088/1748-9326/ad7305\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Research Letters","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1088/1748-9326/ad7305","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Advancing ambient water quality monitoring and management through citizen science in low- and middle-income countries
In contexts where conventional environmental monitoring has historically been limited, citizen science (CS) for monitoring efforts can be an effective approach for decentralized data generation that also raises scientific literacy and environmental awareness. To that end, the United Nations Environmental Program is considering CS as a mechanism for producing ambient water quality data to track progress on sustainable development goal (SDG) indicator 6.3.2: ‘proportion of bodies of water with good ambient water quality’. However, the alignment of SDG 6.3.2 monitoring requirements with CS capacity and results in low- or middle-income countries has not been assessed. Through a systematic literature review of 49 journal publications, complemented by 15 key informant interviews, this article examines the methods and outputs of CS programs in resource-constrained settings. We explore the potential of these programs to contribute to tracking SDG 6.3.2. Using the CS impact assessment framework, we evaluate broader outcomes of CS programs across 5 domains: society, economy, environment, governance, and science and technology. Despite large variability in scope, CS programs were consistently found to generate useful data for national-level reporting on physicochemical and ecological parameters; however, data quality is a concern for CS measurement of microbiological parameters. The focus in literature to-date is predominantly on scientific data production which falls only within the ‘science and technology’ outcome domain. Societal, governance, economic, and environmental outcomes are infrequently evaluated. Of the studies reviewed in this article, 75% identified some form of pollution but only 22% of them reported follow-up actions such as reporting to authorities. While CS has important potential, work is still needed towards the ‘formalization’ of CS, particularly if intended for more vulnerable contexts.
期刊介绍:
Environmental Research Letters (ERL) is a high-impact, open-access journal intended to be the meeting place of the research and policy communities concerned with environmental change and management.
The journal''s coverage reflects the increasingly interdisciplinary nature of environmental science, recognizing the wide-ranging contributions to the development of methods, tools and evaluation strategies relevant to the field. Submissions from across all components of the Earth system, i.e. land, atmosphere, cryosphere, biosphere and hydrosphere, and exchanges between these components are welcome.