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Tuesday, January 7, 2020

Citizen science

From Wikipedia, the free encyclopedia
 
Citizen science (CS; also known as community science, crowd science, crowd-sourced science, civic science, volunteer monitoring, or online citizen science) is scientific research conducted, in whole or in part, by amateur (or nonprofessional) scientists. Citizen science is sometimes described as "public participation in scientific research," participatory monitoring, and participatory action research whose outcomes are often advancements in scientific research, as well as an increase in the public's understanding of science. Based on Alexa rankings iNaturalist is currently the most popular citizen science website followed by eBird and then Zooniverse in second and third place respectively.

Scanning the cliffs near Logan Pass for mountain goats as part of the Glacier National Park Citizen Science Program
 

Definition

The term CS has multiple origins, as well as differing concepts. It was first defined independently in the mid-1990s by Rick Bonney in the United States and Alan Irwin in the United Kingdom. Alan Irwin, a British sociologist, defines CS as "developing concepts of scientific citizenship which foregrounds the necessity of opening up science and science policy processes to the public". Irwin sought to reclaim two dimensions of the relationship between citizens and science: 1) that science should be responsive to citizens' concerns and needs; and 2) that citizens themselves could produce reliable scientific knowledge. The American ornithologist Rick Bonney, unaware of Irwin's work, defined CS as projects in which nonscientists, such as amateur birdwatchers, voluntarily contributed scientific data. This describes a more limited role for citizens in scientific research than Irwin's conception of the term.

The terms citizen science and citizen scientists entered the Oxford English Dictionary (OED) in June 2014. "Citizen science" is defined as "scientific work undertaken by members of the general public, often in collaboration with or under the direction of professional scientists and scientific institutions". "Citizen scientist" is defined as: (a) "a scientist whose work is characterized by a sense of responsibility to serve the best interests of the wider community (now rare)"; or (b) "a member of the general public who engages in scientific work, often in collaboration with or under the direction of professional scientists and scientific institutions; an amateur scientist". The first use of the term "citizen scientist" can be found in the magazine New Scientist in an article about ufology from October 1979.

Muki Haklay cites, from a policy report for the Wilson Center entitled "Citizen Science and Policy: A European Perspective", an alternate first use of the term "citizen science" by R. Kerson in the magazine MIT Technology Review from January 1989. Quoting from the Wilson Center report: "The new form of engagement in science received the name 'citizen science'. The first recorded example of the use of the term is from 1989, describing how 225 volunteers across the US collected rain samples to assist the Audubon Society in an acid-rain awareness raising campaign."

A "Green Paper on Citizen Science" was published in 2013 by the European Commission's Digital Science Unit and Socientize.eu, which included a definition for CS, referring to "the general public engagement in scientific research activities when citizens actively contribute to science either with their intellectual effort or surrounding knowledge or with their tools and resources. Participants provide experimental data and facilities for researchers, raise new questions and co-create a new scientific culture."

Citizen science may be performed by individuals, teams, or networks of volunteers. Citizen scientists often partner with professional scientists to achieve common goals. Large volunteer networks often allow scientists to accomplish tasks that would be too expensive or time consuming to accomplish through other means.

Many citizen-science projects serve education and outreach goals. These projects may be designed for a formal classroom environment or an informal education environment such as museums. 

Citizen science has evolved over the past four decades. Recent projects place more emphasis on scientifically sound practices and measurable goals for public education. Modern citizen science differs from its historical forms primarily in the access for, and subsequent scale of, public participation; technology is credited as one of the main drivers of the recent explosion of citizen science activity.

In March 2015, the Office of Science and Technology Policy published a factsheet entitled "Empowering Students and Others through Citizen Science and Crowdsourcing". Quoting: "Citizen science and crowdsourcing projects are powerful tools for providing students with skills needed to excel in science, technology, engineering, and math (STEM). Volunteers in citizen science, for example, gain hands-on experience doing real science, and in many cases take that learning outside of the traditional classroom setting".

Members of the Cascades Butterfly Citizen Science Team pictured on Sauk mountain
 
In May 2016, a new open-access journal was started by the Citizen Science Association along with Ubiquity Press called Citizen Science: Theory and Practice (CS:T&P). Quoting from the editorial article titled "The Theory and Practice of Citizen Science: Launching a New Journal", "CS:T&P provides the space to enhance the quality and impact of citizen science efforts by deeply exploring the citizen science concept in all its forms and across disciplines. By examining, critiquing, and sharing findings across a variety of citizen science endeavors, we can dig into the underpinnings and assumptions of citizen science and critically analyze its practice and outcomes."

Alternative definitions

Other definitions for citizen science have also been proposed. For example, Bruce Lewenstein of Cornell University's Communication and S&TS departments describes 3 possible definitions:
  • The participation of nonscientists in the process of gathering data according to specific scientific protocols and in the process of using and interpreting that data.
  • The engagement of nonscientists in true decision-making about policy issues that have technical or scientific components.
  • The engagement of research scientists in the democratic and policy process.
Scientists and scholars who have used other definitions include Frank N. von Hippel, Stephen Schneider, Neal Lane and Jon Beckwith. Other alternative terminologies proposed are "civic science" and "civic scientist".

Further, Muki Haklay offers an overview of the typologies of the level of citizen participation in citizen science, which range from "crowdsourcing" (level 1), where the citizen acts as a sensor, to "distributed intelligence" (level 2), where the citizen acts as a basic interpreter, to "participatory science", where citizens contribute to problem definition and data collection (level 3), to "extreme citizen science", which involves collaboration between the citizen and scientists in problem definition, collection and data analysis.

A 2014 Mashable article defines a citizen scientist as: "Anybody who voluntarily contributes his or her time and resources toward scientific research in partnership with professional scientists."

In 2016 the Australian Citizen Science Association released their definition which states "Citizen science involves public participation and collaboration in scientific research with the aim to increase scientific knowledge."

In 2016, the book "Analyzing the Role of Citizen Science in Modern Research" defined citizen science as "work undertaken by civic educators together with citizen communities to advance science, foster a broad scientific mentality, and/or encourage democratic engagement, which allows society to deal rationally with complex modern problems".

Related fields

In a Smart City era, Citizen Science relays on various web-based tools (eg.WebGIS) and becomes Cyber Citizen Science. Some projects, such as SETI@home, use the Internet to take advantage of distributed computing. These projects are generally passive. Computation tasks are performed by volunteers' computers and require little involvement beyond initial setup. There is disagreement as to whether these projects should be classified as citizen science. 

The astrophysicist and Galaxy Zoo co-founder Kevin Schawinski stated: "We prefer to call this [Galaxy Zoo] citizen science because it's a better description of what you're doing; you're a regular citizen but you're doing science. Crowd sourcing sounds a bit like, well, you're just a member of the crowd and you're not; you're our collaborator. You're pro-actively involved in the process of science by participating."

Compared to SETI@home, "Galaxy Zoo volunteers do real work. They're not just passively running something on their computer and hoping that they'll be the first person to find aliens. They have a stake in science that comes out of it, which means that they are now interested in what we do with it, and what we find."

Citizen policy may be another result of citizen science initiatives. Bethany Brookshire (pen name SciCurious) writes: "If citizens are going to live with the benefits or potential consequences of science (as the vast majority of them will), it's incredibly important to make sure that they are not only well informed about changes and advances in science and technology, but that they also ... are able to ... influence the science policy decisions that could impact their lives."

Benefits and limitations

Citizen involvement in scientific projects has become a means of encouraging curiosity and greater understanding of science whilst providing an unprecedented engagement between professional scientists and the general public. In a research report published by the National Park Service in 2008, Brett Amy Thelen and Rachel K. Thiet mention the following concerns, previously reported in the literature, about the validity of volunteer-generated data:
  • Some projects may not be suitable for volunteers, for instance, when they use complex research methods or require a lot of (often repetitive) work.
  • If volunteers lack proper training in research and monitoring protocols, they are at risk of introducing bias into the data.
The question of data accuracy, in particular, remains open. John Losey, who created the Lost Ladybug citizen science project, has argued that the cost-effectiveness of citizen science data can outweigh data quality issues, if properly managed.

In December 2016, authors M. Kosmala, A. Wiggins, A. Swanson and B. Simmons published a study in the journal Frontiers in Ecology and the Environment called "Assessing Data Quality in Citizen Science". The abstract describes how ecological and environmental CS projects have enormous potential to advance science. Also, CS projects can influence policy and guide resource management by producing datasets that are otherwise infeasible to generate. In the section "In a Nutshell" (pg3), four condensed conclusions are stated. They are:
  1. Datasets produced by volunteer CSs can have reliably high quality, on par with those produced by professionals.
  2. Individual volunteer accuracy varies, depending on task difficulty and volunteer experience. Multiple methods exist for boosting accuracy to required levels for a given project.
  3. Most types of bias found in CS datasets are also found in professionally produced datasets and can be accommodated using existing statistical tools.
  4. Reviewers of CS projects should look for iterated project design, standardization and appropriateness of volunteer protocols and data analyses, capture of metadata, and accuracy assessment.
They conclude that as CS continues to grow and mature, a key metric of project success they expect to see will be a growing awareness of data quality. They also conclude that CS will emerge as a general tool helping "to collect otherwise unobtainable high-quality data in support of policy and resource management, conservation monitoring, and basic science."

A study of Canadian lepidoptera datasets published in 2018 compared the use of a professionally curated dataset of butterfly specimen records with four years of data from a CS program, eButterfly. The eButterfly dataset was used as it was determined to be of high quality because of the expert vetting process used on the site, and there existed a historic dataset covering the same geographic area consisting of specimen data, much of it institutional. The authors note that, in this case, CS data provides both novel and complementary information to the specimen data. Five new species were reported from the CS data, and geographic distribution information was improved for over 80% of species in the combined dataset when CS data was included.

Law

In March 2015, the state of Wyoming passed new laws (Senate Files 12 and 80) clarifying that trespassing laws applied even if the trespasser's intention was to gather data to further a U.S. government science program. This hampered some CS researchers who were collecting data while on other people's land. 

Ethics

Various studies have been published that explore the ethics of CS, including issues such as intellectual property and project design.(e.g.) The Citizen Science Association (CSA), based at the Cornell Lab of Ornithology, and the European Citizen Science Association (ECSA), based in the Museum für Naturkunde in Berlin, have working groups on ethics and principles.

In September 2015, the European Citizen Science Association (ECSA) published its Ten Principles of Citizen Science, which have been developed by the "Sharing best practice and building capacity" working group of the ECSA, led by the Natural History Museum, London with input from many members of the association.
  1. Citizen science projects actively involve citizens in scientific endeavour that generates new knowledge or understanding. Citizens may act as contributors, collaborators, or as project leader and have a meaningful role in the project.
  2. Citizen science projects have a genuine science outcome. For example, answering a research question or informing conservation action, management decisions or environmental policy.
  3. Both the professional scientists and the citizen scientists benefit from taking part. Benefits may include the publication of research outputs, learning opportunities, personal enjoyment, social benefits, satisfaction through contributing to scientific evidence e.g. to address local, national and international issues, and through that, the potential to influence policy.
  4. Citizen scientists may, if they wish, participate in multiple stages of the scientific process. This may include developing the research question, designing the method, gathering and analysing data, and communicating the results.
  5. Citizen scientists receive feedback from the project. For example, how their data are being used and what the research, policy or societal outcomes are.
  6. Citizen science is considered a research approach like any other, with limitations and biases that should be considered and controlled for. However unlike traditional research approaches, citizen science provides opportunity for greater public engagement and democratisation of science.
  7. Citizen science project data and meta-data are made publicly available and where possible, results are published in an open access format. Data sharing may occur during or after the project, unless there are security or privacy concerns that prevent this.
  8. Citizen scientists are acknowledged in project results and publications.
  9. Citizen science programmes are evaluated for their scientific output, data quality, participant experience and wider societal or policy impact.
  10. The leaders of citizen science projects take into consideration legal and ethical issues surrounding copyright, intellectual property, data sharing agreements, confidentiality, attribution, and the environmental impact of any activities.
The medical ethics of internet crowdsourcing has been questioned by Graber & Graber in the Journal of Medical Ethics. In particular, they analyse the effect of games and the crowdsourcing project Foldit. They conclude: "games can have possible adverse effects, and that they manipulate the user into participation". 

In March 2019 the online journal Citizen Science: Theory and Practice launched a collection of articles on the theme of Ethical Issues in Citizen Science. The articles are introduced with (quoting): "Citizen science can challenge existing ethical norms because it falls outside of customary methods of ensuring that research is conducted ethically. What ethical issues arise when engaging the public in research? How have these issues been addressed, and how should they be addressed in the future?"

In June 2019, East Asian Science, Technology and Society: An International Journal (EASTS) published an issue titled "Citizen Science: Practices and Problems" which contains 15 articles/studies on CS, including many relevant subjects of which ethics is one. Quoting from the introduction Citizen, Science, and Citizen Science: "The term citizen science has become very popular among scholars as well as the general public, and, given its growing presence in East Asia, it is perhaps not a moment too soon to have a special issue of EASTS on the topic."

Economic worth

In the research paper "Can citizen science enhance public understanding of science?" by Bonney et al. 2016, statistics which analyse the economic worth of citizen science are used, drawn from two papers: i)Sauermann and Franzoni 2015, and ii)Theobald et al. 2015. In "Crowd science user contribution patterns and their implications" by Sauermann and Franzoni (2015), seven projects from the Zooniverse web portal are used to estimate the monetary value of the CS that had taken place. The 7 projects are: Solar Stormwatch, Galaxy Zoo Supernovae, Galaxy Zoo Hubble, Moon Zoo, Old Weather, The Milky Way Project and Planet Hunters. Using data from 180 days in 2010, they find a total of 100,386 users participated, contributing 129,540 hours of unpaid work. Estimating at a rate of $12 an hour (an undergraduate research assistant's basic wage), the total contributions amount to $1,554,474, an average of $222,068 per project. The range over the 7 projects was from $22,717 to $654,130.

In "Global change and local solutions: Tapping the unrealized potential of citizen science for biodiversity research" by Theobald et al. 2015, the authors surveyed 388 unique biodiversity-based projects. Quoting: "We estimate that between 1.36 million and 2.28 million people volunteer annually in the 388 projects we surveyed, though variation is great" and that "the range of in-kind contribution of the volunteerism in our 388 citizen science projects as between $667 million to $2.5 billion annually."

Worldwide participation in citizen science continues to grow. A list of the top five citizen science communities compiled by Marc Kuchner and Kristen Erickson in July 2018 shows a total of 3.75 million participants, although there is likely substantial overlap between the communities. 

Education

There have been studies published which examine the place of CS within education. Teaching aids can include books and activity or lesson plans. Some examples of studies are: 

From the Second International Handbook of Science Education, a chapter entitled: "Citizen Science, Ecojustice, and Science Education: Rethinking an Education from Nowhere" by Mueller and Tippins (2011), acknowledges in the abstract that: "There is an emerging emphasis in science education on engaging youth in citizen science." The authors also ask: "whether citizen science goes further with respect to citizen development." The abstract ends by stating that the "chapter takes account of the ways educators will collaborate with members of the community to effectively guide decisions, which offers promise for sharing a responsibility for democratizing science with others."

From the journal Democracy and Education, an article entitled: "Lessons Learned from Citizen Science in the Classroom" by authors Gray, Nicosia and Jordan (GNJ) (2012) give a response to a study by Mueller, Tippins and Bryan (MTB) called "The Future of Citizen Science". GNJ begins by stating in the abstract that the study The Future of Citizen Science: "provides an important theoretical perspective about the future of democratized science and K12 education." But GRB state: "However, the authors (MTB) fail to adequately address the existing barriers and constraints to moving community-based science into the classroom." They end the abstract by arguing: "that the resource constraints of scientists, teachers, and students likely pose problems to moving true democratized science into the classroom."

In 2014, a study was published called "Citizen Science and Lifelong Learning" by R. Edwards in the journal Studies in the Education of Adults. Edwards begins by writing in the abstract that CS projects have expanded over recent years and engaged CSs and professionals in diverse ways. He continues: "Yet there has been little educational exploration of such projects to date." He describes that "there has been limited exploration of the educational backgrounds of adult contributors to citizen science". Edwards explains that CS contributors are referred to as volunteers, citizens or as amateurs. He ends the abstract: "The article will explore the nature and significance of these different characterisations and also suggest possibilities for further research."

In the journal Microbiology and Biology Education a study was published by Shah and Martinez (2015) called "Current Approaches in Implementing Citizen Science in the Classroom".[73] They begin by writing in the abstract that CS is a partnership between inexperienced amateurs and trained scientists. The authors continue: "With recent studies showing a weakening in scientific competency of American students, incorporating citizen science initiatives in the curriculum provides a means to address deficiencies". They argue that combining traditional and innovative methods can help provide a practical experience of science. The abstract ends: "Citizen science can be used to emphasize the recognition and use of systematic approaches to solve problems affecting the community."

In November 2017, authors Mitchell, Triska and Liberatore published a study in PLOS ONE titled "Benefits and Challenges of Incorporating Citizen Science into University Education". The authors begin by stating in the abstract that CSs contribute data with the expectation that it will be used. It reports that CS has been used for first year university students as a means to experience research. They continue: "Surveys of more than 1500 students showed that their environmental engagement increased significantly after participating in data collection and data analysis." However, only a third of students agreed that data collected by CSs was reliable. A positive outcome of this was that the students were more careful of their own research. The abstract ends: "If true for citizen scientists in general, enabling participants as well as scientists to analyse data could enhance data quality, and so address a key constraint of broad-scale citizen science programs."

History

"Citizen science" is a fairly new term but an old practice. Prior to the 20th century, science was often the pursuit of gentleman scientists, amateur or self-funded researchers such as Sir Isaac Newton, Benjamin Franklin, and Charles Darwin. By the mid-20th century, however, science was dominated by researchers employed by universities and government research laboratories. By the 1970s, this transformation was being called into question. Philosopher Paul Feyerabend called for a "democratization of science". Biochemist Erwin Chargaff advocated a return to science by nature-loving amateurs in the tradition of Descartes, Newton, Leibniz, Buffon, and Darwin—science dominated by "amateurship instead of money-biased technical bureaucrats".

A study from 2016 indicates that the largest impact of citizen science is in research on biology, conservation and ecology, and is utilized mainly as a methodology of collecting and classifying data.

Amateur astronomy

Amateur astronomers can build their own equipment and can hold star parties and gatherings, such as Stellafane.
 
Astronomy has long been a field where amateurs have contributed throughout time, all the way up to the present day.

Collectively, amateur astronomers observe a variety of celestial objects and phenomena sometimes with equipment that they build themselves. Common targets of amateur astronomers include the Moon, planets, stars, comets, meteor showers, and a variety of deep-sky objects such as star clusters, galaxies, and nebulae. Observations of comets and stars are also used to measure the local level of artificial skyglow. One branch of amateur astronomy, amateur astrophotography, involves the taking of photos of the night sky. Many amateurs like to specialize in the observation of particular objects, types of objects, or types of events that interest them.

The American Association of Variable Star Observers has gathered data on variable stars for educational and professional analysis since 1911 and promotes participation beyond its membership on its Citizen Sky website.

Butterfly counts

Butterfly counts have a long tradition of involving individuals in the study of butterflies' range and their relative abundance. Two long-running programs are the UK Butterfly Monitoring Scheme (started in 1976) and the North American Butterfly Association's Butterfly Count Program (started in 1975). There are various protocols for monitoring butterflies and different organizations support one or more of transects, counts and/or opportunistic sightings. eButterfly is an example of a program designed to capture any of the three types of counts for observers in North America. Species-specific programs also exist, with monarchs the prominent example. Two examples of this involve the counting of monarch butterflies during the fall migration to overwintering sites in Mexico: Monarch Watch is a continent-wide project, while (2) the Cape May Monarch Monitoring Project is an example of a local project. The Austrian project Viel-Falter investigated if and how trained and supervised pupils are able to systematically collect data about the occurrence of diurnal butterflies, and how this data could contribute to a permanent butterfly monitoring system. Despite substantial identification uncertainties for some species or species groups, the data collected by pupils was successfully used to predict the general habitat quality for butterflies.

Ornithology

Citizen science projects have become increasingly focused on providing benefits to scientific research. The North American Bird Phenology Program (historically called the Bird Migration and Distribution records) may have been the earliest collective effort of citizens collecting ornithological information in the U.S. The program, dating back to 1883, was started by Wells Woodbridge Cooke. Cooke established a network of observers around North America to collect bird migration records. The Audubon Society's Christmas Bird Count, which began in 1900, is another example of a long-standing tradition of citizen science which has persisted to the present day. Citizen scientists help gather data that will be analyzed by professional researchers, and can be used to produce bird population and biodiversity indicators.

Raptor migration research relies on the data collected by the hawkwatching community. This mostly volunteer group counts migrating accipiters, buteos, falcons, harriers, kites, eagles, osprey, vultures and other raptors at hawk sites throughout North America during the spring and fall seasons. The daily data is uploaded to hawkcount.org where it can be viewed by professional scientists and the public. 

Such indices can be useful tools to inform management, resource allocation, policy and planning. For example, European breeding bird survey data provide input for the Farmland Bird Index, adopted by the European Union as a structural indicator of sustainable development. This provides a cost-effective alternative to government monitoring.

Similarly, data collected by citizen scientists as part of BirdLife Australia's has been analysed to produce the first-ever Australian Terrestrial Bird Indices.

Citizen oceanography

The concept of citizen science has been extended to the ocean environment for characterizing ocean dynamics and tracking marine debris. For example, the mobile app Marine Debris Tracker is a joint partnership of National Oceanic and Atmospheric Administration and the University of Georgia. Long term sampling efforts such as the continuous plankton recorder has been fitted on ships of opportunity since 1931. Plankton collection by sailors and subsequent genetic analysis was pioneered in 2013 by Indigo V Expeditions as a way to better understand marine microbial structure and function.

Coral reefs

Citizen science in Coral reef studies developed in the 21st century.

Underwater photography has become more popular since the early 2000s, resulting on millions of pictures posted every year on various websites and social media. This mass of documentation has great scientific potential, as millions of tourists possess a much superior coverage power than professional scientists, who cannot spend so much time in the field. 

As a consequence, several participative sciences programs have been developed, supported by geotagging and identification web sites (such as iNaturalist.org). The Monitoring through many eyes project collates thousands of underwater images of the Great Barrier Reef and provides an interface for elicitation of reef health indicators.

The National Oceanic and Atmospheric Administration (NOAA) also offers opportunities for volunteer participation. By taking measurements in The United States' National Marine Sanctuaries, citizens contribute data to marine biology projects. In 2016, NOAA benefited from 137,000 hours of research.

There also exist protocols for auto-organization and self-teaching aimed at biodiversity-interested snorkelers, in order for them to turn their observations into sound scientific data, available for research. This kind of approach has been successfully used in Réunion island, allowing for tens of new records and even new species.

Agriculture

Farmer participation in experiments has a long tradition in Agricultural science. There are many opportunities for citizen engagement in different parts of food systems. Citizen science is actively used for crop variety selection for climate adaptation, involving thousands of farmers.

Art history

Citizen science has a long tradition in Natural science. But nowadays, citizen science projects can also be found in various fields of science like Art history. For example, the Zooniverse project AnnoTate is a transcription tool developed to enable volunteers to read and transcribe the personal papers of British-born and émigré artists. The papers are drawn from the Tate Archive. Another example of citizen science in art history is ARTigo. ARTigo collects semantic data on artworks from the footprints left by players of games featuring artwork images. From these footprints, ARTigo automatically builds a semantic search engine for artworks.

Modern technology

Newer technologies have increased the options for citizen science. Citizen scientists can build and operate their own instruments to gather data for their own experiments or as part of a larger project. Examples include amateur radio, amateur astronomy, Six Sigma Projects, and Maker activities. Scientist Joshua Pearce has advocated for the creation of open-source hardware based scientific equipment that both citizen scientists and professional scientists, which can be replicated by digital manufacturing techniques such as 3D printing. Multiple studies have shown this approach radically reduces scientific equipment costs. Examples of this approach include water testing, nitrate and other environmental testing, basic biology and optics. Groups such as Public Lab, which is a community where citizen scientists can learn how to investigate environmental concerns using inexpensive DIY techniques, embody this approach.

Citizen Science Center exhibit in the Nature Research Center wing of the North Carolina Museum of Natural Sciences
 
Video technology is much used in scientific research. The Citizen Science Center in the Nature Research Center wing of the North Carolina Museum of Natural Sciences has exhibits on how to get involved in scientific research and become a citizen scientist. For example, visitors can observe birdfeeders at the Prairie Ridge Ecostation satellite facility via live video feed and record which species they see. 

Since 2005, the Genographic Project has used the latest genetic technology to expand our knowledge of the human story, and its pioneering use of DNA testing to engage and involve the public in the research effort has helped to create a new breed of "citizen scientist". Geno 2.0 expands the scope for citizen science, harnessing the power of the crowd to discover new details of human population history. This includes supporting, organization and dissemination of personal DNA (genetic) testing. Like Amateur astronomy, citizen scientists encouraged by volunteer organizations like the International Society of Genetic Genealogy have provided valuable information and research to the professional scientific community.

With unmanned aerial vehicles, further citizen science is enabled. One example is the ESA's AstroDrone smartphone app for gathering robotic data with the Parrot AR.Drone.

Citizens in Space (CIS), a project of the United States Rocket Academy, seeks to combine citizen science with citizen space exploration. CIS is training citizen astronauts to fly as payload operators on suborbital reusable spacecraft that are now in development. CIS will also be developing, and encouraging others to develop, citizen-science payloads to fly on suborbital vehicles. CIS has already acquired a contract for 10 flights on the Lynx suborbital vehicle, being developed by XCOR Aerospace, and plans to acquire additional flights on XCOR Lynx and other suborbital vehicles in the future.

CIS believes that "The development of low-cost reusable suborbital spacecraft will be the next great enabler, allowing citizens to participate in space exploration and space science."

Internet

The Internet has been a boon to citizen science, particularly through gamification. One of the first Internet-based citizen science experiments was NASA's Clickworkers, which enabled the general public to assist in the classification of images, greatly reducing the time to analyze large data sets. Another was the Citizen Science Toolbox, launched in 2003, of the Australian Coastal Collaborative Research Centre. Mozak is a game in which players create 3D reconstructions from images of actual human and mouse neurons, helping to advance understanding of the brain. One of the largest citizen science games is Eyewire, a brain-mapping puzzle game developed at the Massachusetts Institute of Technology that now has over 200,000 players. Another example is Quantum Moves, a game developed by the Center for Driven Community Research at Aarhus University, which uses online community efforts to solve quantum physics problems. The solutions found by players can then be used in the lab to feed computational algorithms used in building a scalable quantum computer.

More generally, Amazon's Mechanical Turk is frequently used in the creation, collection, and processing of data by paid citizens. There is controversy as to whether or not the data collected through such services is reliable, as it is subject to participants' desire for compensation. However, use of Mechanical Turk tends to quickly produce more diverse participant backgrounds, as well as comparably accurate data when compared to traditional collection methods.

The internet has also enabled citizen scientists to gather data to be analyzed by professional researchers. Citizen science networks are often involved in the observation of cyclic events of nature (phenology), such as effects of global warming on plant and animal life in different geographic areas, and in monitoring programs for natural-resource management. On BugGuide.Net, an online community of naturalists who share observations of arthropod, amateurs and professional researchers contribute to the analysis. By October 2014, BugGuide has over 808,718 images submitted by more than 27,846 contributors.

An NASA/JPL image from the Zooniverse's The Milky Way Project showing a hierarchical bubble structure
 
Not counting iNaturalist and eBird, the Zooniverse is home to the internet's largest, most popular and most successful citizen science projects. The Zooniverse and the suite of projects it contains is produced, maintained and developed by the Citizen Science Alliance (CSA). The member institutions of the CSA work with many academic and other partners around the world to produce projects that use the efforts and ability of volunteers to help scientists and researchers deal with the flood of data that confronts them. On 29 June 2015, the Zooniverse released a new software version with a project-building tool allowing any registered user to create a project. Project owners may optionally complete an approval process to have their projects listed on the Zooniverse site and promoted to the Zooniverse community. A NASA/JPL picture to the right gives an example from one of Zooniverse's projects The Milky Way Project

The website CosmoQuest has as its goal "To create a community of people bent on together advancing our understanding of the universe; a community of people who are participating in doing science, who can explain why what they do matters, and what questions they are helping to answer.

CrowdCrafting enables its participants to create and run projects where volunteers help with image classification, transcription, geocoding and more. The platform is powered by PyBossa software, a free and open-source framework for crowdsourcing.

Project Soothe is a citizen science research project based at the University of Edinburgh. The aim of this research is to create a bank of soothing images, submitted by members of the public, which can be used to help others through psychotherapy and research in the future. Since 2015, Project Soothe has received over 600 soothing photographs from people in 23 countries. Anyone aged 12 years or over are eligible to participate in this research in two ways: (1) By submitting soothing photos that they have taken with a description of why the images make them feel soothed (2) By rating the photos that have been submitted by people worldwide for their soothability. 

Smartphone

The bandwidth and ubiquity afforded by smartphones has vastly expanded the opportunities for citizen science. Examples include iNaturalist, the San Francisco project, the WildLab, Project Noah, and Aurorasurus. Due to their ubiquity, for example, Twitter, Facebook, and smartphones have been useful for citizen scientists, having enabled them to discover and propagate a new type of aurora dubbed "STEVE" in 2016.

There are also apps for monitoring birds, marine wildlife and other organisms, and the "Loss of the Night".

An Android app Sapelli is a mobile data-collection and -sharing platform designed with a particular focus on non-literate and illiterate users. The SPOTTERON app creates synergy effects for projects by sharing a common feature set.

"The Crowd and the Cloud" is a four-part series broadcast during April 2017, which examines citizen science. It shows how smartphones, computers and mobile technology enable regular citizens to become part of a 21st-century way of doing science. The programs also demonstrate how CSs help professional scientists to advance knowledge, which helps speed up new discoveries and innovations. The Crowd & The Cloud is based upon work supported by the National Science Foundation.

Seismology

Since 1975, in order to improve earthquake detection and collect useful information, the European-Mediterranean Seismological Centre monitors the visits of earthquake eyewitnesses to its website and relies on Facebook and Twitter.

Hydrology

Citizen science has been used to provide valuable data in hydrology (catchment science), notably flood risk, water quality and water resource management. A growth in internet use and smartphone ownership has allowed users to collect and share real-time flood-risk information using, for example, social media and web-based forms. Although traditional data collection methods are well-established, citizen science is being used to fill the data gaps on a local level, and is therefore meaningful to individual communities. It has been demonstrated that citizen science is particularly advantageous during a flash flood because the public are more likely to witness these rarer hydrological events than scientists.

Plastics and pollution

Plastic pollution

Citizen science includes projects that help monitor plastics and their associated pollution. These include The Ocean Cleanup, #OneLess, The Big Microplastic Survey, EXXpedition and Alliance to End Plastic Waste. Ellipsis seeks to map the distribution of litter using aerial data mapping by unmanned aerial vehicles and machine learning software. A Zooniverse project called The Plastic Tide (now finished) helped train an algorithm used by Ellipsis.

Projects that use apps include:
  • The European Environment Agency launched an initiative called "Marine Litter Watch" in June 2018. This uses mobile phones to: (quote) "help individuals and communities come together to clean up Europe’s beaches."
  • PlasticPatrol seeks to log and record plastic pollution: (quote) "The Plastic Patrol app is a real world tool that combines citizen science and scientific analysis to help us gather crucial insight into plastic pollution."
  • Litterati's mission is to eradicate litter: (quote) "When millions of people come together, the impossible becomes reality, and change happens."
  • Anecdata helps anyone and any organisation to create a project: (quote) "Anecdata helps individuals and organizations collect, manage, and share their citizen science data, providing both web-based and mobile solutions for gathering and accessing observations."
  • In the UK #2minutebeachclean seeks to purge plastics in coastal environments. They offer an app and a beachclean board, which can be displayed on beaches: (quote) "We believe that every piece of litter removed from the beach matters. So it doesn’t matter if you do 2 minutes or 30."
Examples of relevant articles (by date):
  • Citizen Science Promotes Environmental Engagement: (quote) "Citizen science projects are rapidly gaining popularity among the public, in which volunteers help gather data on species that can be used by scientists in research. And it’s not just adults who are involved in these projects – even kids have collected high-quality data in the US."
  • Tackling Microplastics on Our Own: (quote) "Plastics, ranging from the circles of soda can rings to microbeads the size of pinheads, are starting to replace images of sewage for a leading cause of pollution – especially in the ocean". Further, "With recent backing from the Crowdsourcing and Citizen Science Act, citizen science is increasingly embraced as a tool by US Federal agencies."
  • Citizen Scientists Are Tracking Plastic Pollution Worldwide: (quote) "Scientists who are monitoring the spread of tiny pieces of plastic throughout the environment are getting help from a small army of citizen volunteers – and they’re finding bits of polymer in some of the most remote parts of North America."
  • Artificial intelligence and citizen scientists: Powering the clean-up of Asia Pacific’s beaches:(quote) "The main objective is to support citizen scientists cleaning up New Zealand beaches and get a better understanding of why litter is turning up, so preventive and proactive action can be taken."
  • Citizen science could help address Canada's plastic pollution problem: (quote) "But citizen engagement and participation in science goes beyond beach cleanups, and can be used as a tool to bridge gaps between communities and scientists. These partnerships between scientists and citizen scientists have produced real world data that have influenced policy changes."
Examples of relevant scientific studies or books include (by date):
  • Distribution and abundance of small plastic debris on beaches in the SE Pacific (Chile): a study supported by a citizen science project: (quote) "The citizen science project "National Sampling of Small Plastic Debris" was supported by schoolchildren from all over Chile who documented the distribution and abundance of small plastic debris on Chilean beaches. Thirty-nine schools and nearly 1000 students from continental Chile and Easter Island participated in the activity."
  • Incorporating citizen science to study plastics in the environment: (quote) "Taking advantage of public interest in the impact of plastic on the marine environment, successful Citizen Science (CS) programs incorporate members of the public to provide repeated sampling for time series as well as synoptic collections over wide geographic regions."
  • Marine anthropogenic litter on British beaches: A 10-year nationwide assessment using citizen science data: (quote) "Citizen science projects, whereby members of the public gather information, offer a low-cost method of collecting large volumes of data with considerable temporal and spatial coverage. Furthermore, such projects raise awareness of environmental issues and can lead to positive changes in behaviours and attitudes."
  • Determining Global Distribution of Microplastics by Combining Citizen Science and In-Depth Case Studies: (quote) "Our first project involves the general public through citizen science. Participants collect sand samples from beaches using a basic protocol, and we subsequently extract and quantify microplastics in a central laboratory using the standard operating procedure."
  • Risk Perception of Plastic Pollution: Importance of Stakeholder Involvement and Citizen Science: (quote) "The chapter finally discusses how risk perception can be improved by greater stakeholder involvement and utilization of citizen science and thereby improve the foundation for timely and efficient societal measures."
  • Assessing the citizen science approach as tool to increase awareness on the marine litter problem:(quote) "This paper provides a quantitative assessment of students' attitude and behaviors towards marine litter before and after their participation to SEACleaner, an educational and citizen science project devoted to monitor macro- and micro-litter in an Area belonging to Pelagos Sanctuary."
  • Spatial trends and drivers of marine debris accumulation on shorelines in South Eleuthera, The Bahamas using citizen science: (quote) "This study measured spatial distribution of marine debris stranded on beaches in South Eleuthera, The Bahamas. Citizen science, fetch modeling, relative exposure index and predictive mapping were used to determine marine debris source and abundance."
  • Making citizen science count: Best practices and challenges of citizen science projects on plastics in aquatic environments:(quote) "Citizen science is a cost-effective way to gather data over a large geographical range while simultaneously raising public awareness on the problem".
  • White and wonderful? Microplastics prevail in snow from the Alps to the Arctic: (quote) ""In March 2018, five samples were taken at different locations on Svalbard (Fig. 1A and Table 1) by citizen scientists embarking on a land expedition by ski-doo (Aemalire project). The citizens were instructed on contamination prevention and equipped with protocol forms, prerinsed 2-liter stainless steel containers (Ecotanca), a porcelain mug, a steel spoon, and a soup ladle for sampling."

Citizen sensing

Citizen sensing can be a form of Citizen science: (quote) "The work of citizen sensing, as a form of citizen science, then further transforms Stengers’s notion of the work of science by moving the experimental facts and collectives where scientific work is undertaken out of the laboratory of experts and into the world of citizens." Similar sensing activities include Crowdsensing and Participatory monitoring. While the idea of using mobile technology to aid this sensing is not new, creating devices and systems that can be used to aid regulation has not been straightforward. Some examples of projects that include citizen sensing are:
  • Citizen Sense (2013-2018): (quote) "Practices of monitoring and sensing environments have migrated to everyday participatory applications, where users of smart phones and networked devices are able to engage with modes of environmental observation and data collection."
  • Breathe Project: (quote) "We use the best available science and technology to better understand the quality of the air we breathe and provide opportunities for citizens to engage and take action."
  • The Bristol Approach to Citizen Sensing: (quote) "Citizen Sensing is about empowering people and places to understand and use smart tech and data from sensors to tackle the issues they care about, connect with other people who can help, and take positive, practical action."
  • Luftdaten.info: (quote) "You and thousands of others around the world install self-built sensors on the outside their home. Luftdaten.info generates a continuously updated particular matter map from the transmitted data."
  • CitiSense: (quote) "CitiSense aims to co-develop a participatory risk management system (PRMS) with citizens, local authorities and organizations which enables them to contribute to advanced climate services and enhanced urban climate resilience as well as receive recommendations that support their security."

Around the world


Africa

  • In South Africa (SA), CS projects include: the Stream Assessment Scoring System (miniSASS) which "encourages enhanced catchment management for water security in a climate stressed society."
Snapshot Serengeti classifies animals at the Serengeti National Park in Tanzania
  • Also in SA, "Members of the public, or 'citizen scientists' are helping researchers from the University of Pretoria to identify Phytophthora species present in the fynbos."
  • In June 2016, citizen science experts from across East Africa gathered in Nairobi, Kenya for a symposium organised by the Tropical Biology Association (TBA) in partnership with the Centre for Ecology & Hydrology (CEH). The aim was "to harness the growing interest and expertise in East Africa to stimulate new ideas and collaborations in citizen science." Rosie Trevelyan of the TBA said: "We need to enhance our knowledge about the status of Africa's species and the threats facing them. And scientists can't do it all on their own. At the same time, citizen science is an extremely effective way of connecting people more closely to nature and enrolling more people in conservation action".
  • The website Zooniverse hosts several African CS projects, including: Snapshot Serengeti, Wildcam Gorongosa and Jungle Rhythms.
  • Nigeria has the Ibadan Bird Club whose to aim is to "exchange ideas and share knowledge about birds, and get actively involved in the conservation of birds and biodiversity."
  • In Namibia, Giraffe Spotter.org is "project that will provide people with an online citizen science platform for giraffes".
  • Within the Republic of the Congo, the territories of an indigenous people have been mapped so that "the Mbendjele tribe can protect treasured trees from being cut down by logging companies". An Android open-source app called Sapelli was used by the Mbendjele which helped them map "their tribal lands and highlighted trees that were important to them, usually for medicinal reasons or religious significance. Congolaise Industrielle des Bois then verified the trees that the tribe documented as valuable and removed them from its cutting schedule. The tribe also documented illegal logging and poaching activities."
  • In West Africa, the eradication of the recent outbreak of Ebola virus disease was partly helped by CS. "Communities learnt how to assess the risks posed by the disease independently of prior cultural assumptions, and local empiricism allowed cultural rules to be reviewed, suspended or changed as epidemiological facts emerged." "Citizen science is alive and well in all three Ebola-affected countries. And if only a fraction of the international aid directed at rebuilding health systems were to be redirected towards support for citizen science, that might be a fitting memorial to those who died in the epidemic."

Asia

  • The Hong Kong Birdwatching Society was established in 1957, and is the only local civil society aiming at appreciating and conserving Hong Kong birds and their natural environment. Their bird surveys go back to 1958, and they carry out a number of Citizen Science events such as their yearly sparrow census.
  • The Bird Count India partnership consists of a large number of organizations and groups involved in birdwatching and bird surveys. They coordinate a number of Citizen Science projects such as the Kerala Bird Atlas and Mysore city Bird Atlas that map the distribution and abundance of birds of entire Indian states.
  • The Taiwan Roadkill Observation Network, founded in 2011 and consists of more than 16,000 members as of 2019, is a Citizen Science project where roadkill across Taiwan is photographed and sent to the Endemic Species Research Institute for study. Its primary goal has been to set up an eco-friendly path to mitigate roadkill challenges and popularize national discourse on environmental issues and civil participation in scientific research. The members of the Taiwan Roadkill Observation Network volunteer to observe the animals’ corpses caused by roadkill or other reasons in Taiwan, and upload pictures and geographic locations of the roadkill to an internet database or send the corpses to the Endemic Species Research for making specimen. Because the members come from different areas of the island, the collection of data could serve as an animal distribution map of the island. According to the geographical data and pictures of dead animals collected by the members, the community itself and the sponsor the Endemic Species Center could find out the hotspots and the reasons of animals’ death. One of the most renowned case is that the community successfully detected rabies cases due to the massively collected data and the corpse of Melogale moschata have been accumulated for years and alarmed the government authority to take actions to prevent the prevalence of rabies in Taiwan immediately. Another case in 2014 that some citizen scientists discovered birds that died from unknown causes near an agricultural area, then Taiwan Roadkill Observation Network cooperated with National Pingtung University of Science and Technology and engaged citizen scientists to collect bird carcass. The volunteers collected 250 bird corpses for laboratory tests, which confirmed that the bird deaths were attributable to the pesticides used on crops. This prompted the Taiwanese government to restrict pesticides, and the Bill of Pesticide Management amendment, establishing a pesticide control system, was passed after the third reading in the Legislative Yuan. The results indicated that Taiwan Roadkill Observation Network developed a set of shared working methods and jointly completed certain actions. Furthermore, the community of Taiwan Roadkill Observation Network have made real changes on road resign to avoid roadkill, improved the management of usage of pesticide, epidemic prevention, and so on.
  • The AirBox Project was launched in Taiwan to create a participatory ecosystem with a focus on PM2.5 monitoring with AirBox devices. At the end of 2014, the public paid more attention to the PM2.5 level because the air pollution problem became worse, especially in central and southern Taiwan. High PM2.5 level is harmful to our health, such as respiratory problems, so it aroused public concerns and led to an intensive debate about air pollution sources. Some experts indicated that the air quality was affected by pollutants from Mainland China, while some environmentalists believed that it is the result of industrialization such as exhaust fumes from local power plants or factories; however, no one knew the answer because of insufficient data. Dr. Ling-Jyh Chen, a researcher of the Institute of Information Science, Academia Sinica, launched The AirBox Project. His original idea is inspired by a popular Taiwanese slogan Save Your Environment by Yourself. As an expert in Participatory Sensing System, he decided to take this bottom-up approach to collect PM2.5 level data, and through open data and data analysis to have a better understanding of the possible air pollution source. In this ecosystem, massive data was collected from the AirBox device. Data was instantly revealed online to inform people of PM2.5 level so that they take proper action, such as wearing a mask or staying at home, to prevent themselves from directly exploring to polluted environment. Data could be also analyzed to understand the possible sources of pollution and provide recommendations for improving the situation. To be precise, there are four main steps in this project. I) Develop the AirBox device. Developing a device that could correctly collect the data of the PM2.5 level was time-consuming. It took more than three years to develop AirBox that can be easily used, but with both high accuracy and low cost. II) Broad installation of AirBox. In the beginning, very few people were willing to install it at their homes because of their concerns about the possible harm to their health, power-consuming problem and maintenances of it, so that AirBoxs were only installed in a relatively small area. Thanks to the help from Taiwan’s LASS (Location Aware Sensing System) community, AirBox appeared in all parts of Taiwan. As of February 2017, there are more than 1,600 Air Boxes installed in more than 27 countries. III) Open Source and Data Analysis. All measurement results were released and visualized in real-time to the public through different media, such as their website and Facebook page. Data can be analyzed to trace pollution sources.
  • Japan has a long history of citizen science involvement, the 1,200-year-old tradition of collecting records on cherry blossom flowering probably being the world's longest-running citizen science project. One of the most influential citizen science projects has also come out of Japan: Safecast. Dedicated to open citizen science for the environment, Safecast was established in the wake of the Fukushima nuclear disaster, and produces open hardware sensors for radiation and air-pollution mapping. Presenting this data via a global open data network and maps

South America

Asháninka children in school
  • In 2015 the Asháninka people from Apiwtxa, which crosses the border between Brazil and Peru, began using the Android app Sapelli to monitor their land. The Ashaninka have "faced historical pressures of disease, exploitation and displacement, and today still face the illegal invasion of their lands by loggers and hunters. This monitoring project shows how the Apiwtxa Ashaninka from the Kampa do Rio Amônia Indigenous Territory, Brazil, are beginning to use smartphones and technological tools to monitor these illegal activities more effectively."
  • In Argentina, two smartphone Android applications are available for CS. i) AppEAR has been developed at the Institute of Limnology and was launched in May 2016. Joaquín Coachman is a researcher who developed an "application that appeals to the collaboration of users of mobile devices in collecting data that allow the study of aquatic ecosystems" (translation). Coachman stated: "Not much of citizen science in Argentina, just a few more oriented to astronomy specific cases. As ours is the first. And I have volunteers from different parts of the country that are interested in joining together to centralize data. That's great because these types of things require many people participate actively and voluntarily" (translation). ii) eBird was launched in 2013, and has so far identified 965 species of birds. eBird in Argentina is "developed and managed by the Cornell Lab of Ornithology at Cornell University, one of the most important ornithological institutions in the world, and locally presented recently with the support of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCyT)" (translation).
  • Projects in Brazil include: i) Platform and mobile app 'Missions' has been developed by IBM in their São Paulo research lab with Brazil's Ministry for Environment and Innovation (BMEI). Sergio Borger, an IBM team lead in São Paulo, devised the crowdsourced approach when BMEI approached the company in 2010. They were looking for a way to create a central repository for the rainforest data. Users can upload photos of a plant species and its components, enter its characteristics (such as color and size), compare it against a catalog photo and classify it. The classification results are juried by crowdsourced ratings. ii) Exoss Citizen Science is a member of Astronomers Without Borders and seeks to explore the southern sky for new meteors and radiants. Users can report meteor fireballs through uploading pictures on to a webpage or by linking to YouTube.
  • A jaguar in Pantanal; an example of Brazilian biodiversity.
    iii) The Information System on Brazilian Biodiversity (SiBBr) was launched in 2014 "aiming to encourage and facilitate the publication, integration, access and use of information about the biodiversity of the country." Their initial goal "was to gather 2.5 million occurrence records of species from biological collections in Brazil and abroad up to the end of 2016. It is now expected that SiBBr will reach nine million records in 2016." Andrea Portela said: "In 2016, we will begin with the citizen science. They are tools that enable anyone, without any technical knowledge, to participate. With this we will achieve greater engagement with society. People will be able to have more interaction with the platform, contribute and comment on what Brazil has. iv) The Brazilian Marine Megafauna Project (Iniciativa Pro Mar) is working with the European CSA towards its main goal, which is the "sensibilization of society for marine life issues" and concerns about pollution and the over-exploitation of natural resources. Having started as a project monitoring manta ray, it now extends to whale shark and educating schools and divers within the Santos area. Its social media activities include a live streaming of a CS course to help divers identify marine megafauna. v) A smartphone app called Plantix has been developed by the Leibniz Centre for Agricultural Landscape Research (ZALF) which helps Brazilian farmers discover crop diseases quicker and helps fight them more efficiently. Brazil is a very large agricultural exporter, but between 10-30% of crops fail because of disease. "The database currently includes 175 frequently occurring crop diseases and pests as well as 40,000 photos. The identification algorithm of the app improves with every image which records a success rate of over 90 per cent as of approximately 500 photos per crop disease." vi) In an Atlantic Ocean forest region in Brazil, an effort to map the genetic riches of soil is under way. The Drugs From Dirt initiative, based at the Rockefeller University, seeks to turn up bacteria that yield new types of antibiotics- the Brazilian region being particularly rich in potentially useful bacterial genes. Approximately a quarter of the 185 soil samples have been taken by Citizen Scientists without which the project could not run.
  • In Chile CS projects include (some websites in Spanish): i) Testing new cancer therapies with scientists from the Science Foundation for Life. ii) Monitoring the population of the Chilean bumblebee. iii) Monitoring the invasive ladybird Chinita arlequín. iv) Collecting rain water data. v) Monitoring various pollinating fly populations. vi) Providing information and field data on the abundance and distribution of various species of rockfish.
  • Projects in Colombia include (some websites in Spanish): i) The Communications Project of the Humboldt Institute along with the Organization for Education and Environmental Protection initiated projects in the Bogotá wetlands of Cordoba and El Burro, which have a lot of biodiversity. ii) In the Model Forest of Risaralda, the Colombia 'proyecto de Ciencia Abierta y Colaborativa' promotes citizen participation in research related to how the local environment is adapting to climate change. The first meeting took place in the Flora and Fauna Sanctuary Otún Quimbaya. iii) The Citizen Network Environmental Monitoring (CLUSTER), based in the city of Bucaramanga, seeks to engage younger students in data science, who are trained in building weather stations with open repositories based on free software and open hardware data. iv) The Symposium on Biodiversity has adapted the CS tool iNaturalist for use in Colombia. v) The Sinchi Amazonic Institute of Scientific Research seeks to encourage the development and diffusion of knowledge, values and technologies on the management of natural resources for ethnic groups in the Amazon. This research should further the use of participatory action research schemes and promoting participation communities.
  • Since 2010, the Pacific Biodiversity Institute (PBI) seeks "volunteers to help identify, describe and protect wildland complexes and roadless areas in South America". The PBI "are engaged in an ambitious project with our Latin American conservation partners to map all the wildlands in South America, to evaluate their contribution to global biodiversity and to share and disseminate this information."

Conferences

The first Conference on Public Participation in Scientific Research was held in Portland, Oregon in August 2012. Citizen science is now often a theme at large conferences, such as the annual meeting of the American Geophysical Union.

In 2010, 2012 and 2014 there were three Citizen Cybersience summits, organised by the Citizen Cyberscience Centre in Geneva and University College London. The 2014 summit was hosted in London and attracted over 300 participants.

In January 2015, the ETH Zürich and University of Zürich hosted an international meeting on the "Challenges and Opportunities in Citizen Science".

The first citizen science conference hosted by the Citizen Science Association was in San Jose, California, in February 2015 in partnership with the AAAS conference. The Citizen Science Association conference, CitSci 2017, was held in Saint Paul, Minnesota, United States, between 17 and 20 May 2017. The conference had more than 600 attendees. The next CitSci is in March 2019 in Raleigh, USA.

The platform "Österreich forscht" hosts the annual Austrian citizen science conference since 2015.

Carbon monitoring

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Carbon_monitoring

Carbon monitoring refers to tracking how much carbon dioxide or methane is produced by particular activity at a particular point in time. For example, it may refer to tracking methane emissions from agriculture, or carbon dioxide emissions from land use changes, such as deforestation, or from burning fossil fuels, whether in a power plant, automobile, or other device. Because carbon dioxide is the greenhouse gas emitted in the largest quantities, and methane is an even more potent greenhouse gas, monitoring carbon emissions is widely seen as crucial to any effort to reduce emissions and thereby slow climate change. Monitoring carbon emissions is key to the cap-and-trade program currently being used in Europe, as well as the one in California, and will be necessary for any such program in the future, like the Paris Agreement. The lack of reliable sources of consistent data on carbon emissions is a significant barrier to efforts to reduce emissions.

Data sources

Sources of such emissions data include:

Carbon Monitoring for Action (CARMA) – An online database provided by the Center for Global Development, that includes plant-level emissions for more than 50,000 power plants and 4,000 power companies around the world, as well as the total emissions from power generation of countries, provinces (or states), and localities. Carbon emissions from power generation account for about 25 percent of global CO
2
emissions.

ETSWAP - An emissions monitoring and reporting system currently in use in the UK and Ireland, which enables relevant organizations to monitor, verify and report carbon emissions, as is required by the EU ETS (European Union Emissions Trading Scheme).

FMS - A system used in Germany to record and calculate annual emission reports for plant operators subject to the EU ETS.

In the United States

Almost all climate change regulations in the US have stipulations to reduce carbon dioxide and methane emissions by economic sector, so being able to accurately monitor and assess these emissions is crucial to being able to assess compliance with these regulations. Emissions estimates at the national level have been shown to be fairly accurate, but at the state level there is still much uncertainty. As part of the Paris Agreement, the US pledged to "decrease its GHG emissions by 26–28 % relative to 2005 levels by 2025 as part of the Paris Agreement negotiated at COP21. To comply with these regulations, it is necessary to quantify emissions from specific source sectors. A source sector is a sector of the economy that emits a particular greenhouse gas, i.e. methane emissions from the oil and gas industry, which the US has pledged to decrease by 40–45 % relative to 2012 levels by 2025 as a more specific action towards achieving its Paris Agreement contribution.

Currently, most governments, including the US government, estimate carbon emissions with a "bottom-up" approach, using emission factors which give the rate of carbon emissions per unit of a certain activity, and data on how much of that activity has taken place. For example an emission factor can be determined for the amount of carbon dioxide emitted per gallon of gasoline burned, and this can be combined with data on gasoline sales to get an estimate of carbon emissions from light duty vehicles. Other examples include determining the number of cows in various locations, or the mass of coal burned at power plants, and combining these data with the appropriate emissions factors to estimate methane or carbon dioxide emissions. Sometimes "top-down" methods are used to monitor carbon emissions. These involve measuring the concentration of a greenhouse gas in the atmosphere and using these measurements to determine the distribution of emissions which caused the resulting concentrations.

Accounting by sector can be complicated when there is a chance of double counting. For example, when coal is gasified to produce synthetic natural gas, which is then mixed with natural gas and burned at a natural gas powered power plant, if accounted for as part of the natural gas sector, this activity must be subtracted from the coal sector and added to the natural gas sector in order to be properly accounted for.

NASA Carbon Monitoring System (CMS)

NASA Carbon Monitoring System (CMS) is a climate research program created by a congressional order in 2010 that provides grants of about $500,000 a year for climate research that measure carbon dioxide and methane emissions. Using instruments in satellites and airplanes CMS funded research projects provide data to the United States and other countries that help track progress of individual nations regarding their Paris climate emission cuts agreements. For example, CMS projects measured carbon emissions from deforestation and forest degradation. CMS "stitch-ed] together observations of sources and sinks into high-resolution models of the planet's flows of carbon." The 2019 federal budget specifically assured funding for CMS, after President Trump ended funding in April, 2018.

In the European Union

As part of the European Union Emission Trading Scheme (EU-ETS), carbon monitoring is necessary in order to ensure compliance with the cap-and-trade program. This carbon monitoring program has three main components: atmospheric carbon dioxide measurements, bottom-up carbon dioxide emissions maps, and an operational data-assimilation system to synthesize the information from the first two components.

The top-down, atmospheric measurement approach involves satellite data and in-situ measurements of carbon dioxide concentrations, as well as atmospheric models that model atmospheric transport of carbon dioxide. These have limited ability to determine carbon dioxide emissions at highly resolved spatial scales and can typically not represent finer scales than a 1 km grid. The models also must resolve the fluxes of carbon dioxide from anthropogenic sources like fossil fuel burning, and from natural interactions like terrestrial ecosystems and the ocean. Due to the complexities and limitations of the top-down approach, the EU combines this method with a bottom-up approach.

The current bottom-up data are based on information that is self-reported by emitters in the trading scheme. However, the EU is trying to improve this information source and has proposed plans for improved bottom-up emissions maps, which will have greatly improved spatial resolution and near real-time updates.

An operational data system to combine the information gathered from the two aforementioned sources is also planned. The EU hopes that by the 2030s, this will be operational and enable a highly sophisticated carbon monitoring program across the European Union.

Satellites

Satellites can be used to monitor carbon dioxide concentrations from outer space, and have been shown to be as accurate as Earth-based measurement systems. NASA currently operates a satellite named the Orbiting Carbon Observatory-2 (OCO-2), and Japan operates their own satellite, the Greenhouse Gases Observing Satellite (GOSAT). These satellites can provide valuable information to fill in data gaps from emission inventories. The OCO-2 measured a strong flux of carbon dioxide over the Middle East, which had not been represented in emissions inventories, indicating that important sources were being neglected in bottom-up estimates of emissions. These satellites currently both have an error of only 0.5% in the measurements, but the American and Japanese teams hope to bring that error down to 0.25%. China recently launched their own satellite to monitor greenhouse gas concentrations on Earth, the TanSat, in December 2016. It currently has a three-year mission planned and will take readings of carbon dioxide concentrations every 16 days.

Environmental monitoring

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Environmental_monitoring

Environmental monitoring describes the processes and activities that need to take place to characterize and monitor the quality of the environment. Environmental monitoring is used in the preparation of environmental impact assessments, as well as in many circumstances in which human activities carry a risk of harmful effects on the natural environment. All monitoring strategies and programs have reasons and justifications which are often designed to establish the current status of an environment or to establish trends in environmental parameters. In all cases, the results of monitoring will be reviewed, analyzed statistically, and published. The design of a monitoring program must therefore have regard to the final use of the data before monitoring starts.

Air quality monitoring

Air quality monitoring station

Air pollutants are atmospheric substances—both naturally occurring and anthropogenic—which may potentially have a negative impact on the environment and organism health. With the evolution of new chemicals and industrial processes has come the introduction or elevation of pollutants in the atmosphere, as well as environmental research and regulations, increasing the demand for air quality monitoring.

Air quality monitoring is challenging to enact as it requires the effective integration of multiple environmental data sources, which often originate from different environmental networks and institutions. These challenges require specialized observation equipment and tools to establish air pollutant concentrations, including sensor networks, geographic information system (GIS) models, and the Sensor Observation Service (SOS), a web service for querying real-time sensor data. Air dispersion models that combine topographic, emissions, and meteorological data to predict air pollutant concentrations are often helpful in interpreting air monitoring data. Additionally, consideration of anemometer data in the area between sources and the monitor often provides insights on the source of the air contaminants recorded by an air pollution monitor.

Air quality monitors are operated by citizens, regulatory agencies, and researchers to investigate air quality and the effects of air pollution. Interpretation of ambient air monitoring data often involves a consideration of the spatial and temporal representativeness of the data gathered, and the health effects associated with exposure to the monitored levels. If the interpretation reveals concentrations of multiple chemical compounds, a unique "chemical fingerprint" of a particular air pollution source may emerge from analysis of the data.

Air sampling

Passive or "diffusive" air sampling depends on meteorological conditions such as wind to diffuse air pollutants to a sorbent medium. Passive samplers have the advantage of typically being small, quiet, and easy to deploy, and they are particularly useful in air quality studies that determine key areas for future continuous monitoring.

Air pollution can also be assessed by biomonitoring with organisms that bioaccumulate air pollutants, such as lichens, mosses, fungi, and other biomass. One of the benefits of this type of sampling is how quantitative information can be obtained via measurements of accumulated compounds, representative of the environment from which they came. However, careful considerations must be made in choosing the particular organism, how it's dispersed, and relevance to the pollutant.

Other sampling methods include the use of a denuder, needle trap devices, and microextraction techniques.

Soil monitoring

Collecting a soil sample in Mexico for pathogen testing

Soil monitoring involves the collection and/or analysis of soil and its associated quality, constituents, and physical status to determine or guarantee its fitness for use. Soil faces many threats, including compaction, contamination, organic material loss, biodiversity loss, slope stability issues, erosion, salinization, and acidification. Soil monitoring helps characterize these threats and other potential risks to the soil, surrounding environments, animal health, and human health.

Assessing these threats and other risks to soil can be challenging due to a variety of factors, including soil's heterogeneity and complexity, scarcity of toxicity data, lack of understanding of a contaminant's fate, and variability in levels of soil screening. This requires a risk assessment approach and analysis techniques that prioritize environmental protection, risk reduction, and, if necessary, remediation methods. Soil monitoring plays a significant role in that risk assessment, not only aiding in the identification of at-risk and affected areas but also in the establishment of base background values of soil.

Soil monitoring has historically focused on more classical conditions and contaminants, including toxic elements (e.g., mercury, lead, and arsenic) and persistent organic pollutants (POPs). Historically, testing for these and other aspects of soil, however, has had its own set of challenges, as sampling in most cases is of a destructive in nature, requiring multiple samples over time. Additionally, procedural and analytical errors may be introduced due to variability among references and methods, particularly over time. However, as analytical techniques evolve and new knowledge about ecological processes and contaminant effects disseminate, the focus of monitoring will likely broaden over time and the quality of monitoring will continue to improve.

Soil sampling

The two primary types of soil sampling are grab sampling and composite sampling. Grab sampling involves the collection of an individual sample at a specific time and place, while composite sampling involves the collection of a homogenized mixture of multiple individual samples at either a specific place over different times or multiple locations at a specific time. Soil sampling may occur both at shallow ground levels or deep in the ground, with collection methods varying by level collected from. Scoops, augers, core barrel, and solid-tube samplers, and other tools are used at shallow ground levels, whereas split-tube, solid-tube, or hydraulic methods may be used in deep ground.

Monitoring programs

A portable X-ray fluorescence (XRF) analyzer can be used in the field for testing soils for metal contamination
 

Soil contamination monitoring

Soil contamination monitoring helps researchers identify patterns and trends in contaminant deposition, movement, and effect. Human-based pressures such as tourism, industrial activity, urban sprawl, construction work, and inadequate agriculture/forestry practices can contribute to and make worse soil contamination and lead to the soil becoming unfit for its intended use. Both inorganic and organic pollutants may make their way to the soil, having a wide variety of detrimental effects. Soil contamination monitoring is therefore important to identify risk areas, set baselines, and identify contaminated zones for remediation. Monitoring efforts may range from local farms to nationwide efforts, such as those made by China in the late 2000s, providing details such as the nature of contaminants, their quantity, effects, concentration patterns, and remediation feasibility. Monitoring and analytical equipment will ideally will have high response times, high levels of resolution and automation, and a certain degree of self-sufficiency. Chemical techniques may be used to measure toxic elements and POPs using chromatography and spectrometry, geophysical techniques may assess physical properties of large terrains, and biological techniques may use specific organisms to gauge not only contaminant level but also byproducts of contaminant biodegradation. These techniques and others are increasingly becoming more efficient, and laboratory instrumentation is becoming more precise, resulting in more meaningful monitoring outcomes.

Soil erosion monitoring

Soil erosion monitoring helps researchers identify patterns and trends in soil and sediment movement. Monitoring programs have varied over the years, from long-term academic research on university plots to reconnaissance-based surveys of biogeoclimatic areas. In most methods, however, the general focus is on identifying and measuring all the dominant erosion processes in a given area. Additionally, soil erosion monitoring may attempt to quantify the effects of erosion on crop productivity, though challenging "because of the many complexities in the relationship between soils and plants and their management under a variable climate."

Soil salinity monitoring

Soil salinity monitoring helps researchers identify patterns and trends in soil salt content. Both the natural process of seawater intrusion and the human-induced processes of inappropriate soil and water management can lead to salinity problems in soil, with up to one billion hectares of land affected globally (as of 2013). Salinity monitoring at the local level may look closely at the root zone to gauge salinity impact and develop management options, whereas at the regional and national level salinity monitoring may help with identifying areas at-risk and aiding policymakers in tackling the issue before it spreads. The monitoring process itself may be performed using technologies such as remote sensing and geographic information systems (GIS) to identify salinity via greenness, brightness, and whiteness at the surface level. Direct analysis of soil up close, including the use of electromagnetic induction techniques, may also be used to monitor soil salinity.

Water quality monitoring

Electrofishing survey methods use a mild electric shock to temporarily stun fish for capture, identification and counting. The fish are then returned to the water unharmed.
 

Design of environmental monitoring programmes

Water quality monitoring is of little use without a clear and unambiguous definition of the reasons for the monitoring and the objectives that it will satisfy. Almost all monitoring (except perhaps remote sensing) is in some part invasive of the environment under study and extensive and poorly planned monitoring carries a risk of damage to the environment. This may be a critical consideration in wilderness areas or when monitoring very rare organisms or those that are averse to human presence. Some monitoring techniques, such as gill netting fish to estimate populations, can be very damaging, at least to the local population and can also degrade public trust in scientists carrying out the monitoring. 

Almost all mainstream environmentalism monitoring projects form part of an overall monitoring strategy or research field, and these field and strategies are themselves derived from the high levels objectives or aspirations of an organisation. Unless individual monitoring projects fit into a wider strategic framework, the results are unlikely to be published and the environmental understanding produced by the monitoring will be lost. 

Parameters


Chemical

Analyzing water samples for pesticides
 
The range of chemical parameters that have the potential to affect any ecosystem is very large and in all monitoring programmes it is necessary to target a suite of parameters based on local knowledge and past practice for an initial review. The list can be expanded or reduced based on developing knowledge and the outcome of the initial surveys.

Freshwater environments have been extensively studied for many years and there is a robust understanding of the interactions between chemistry and the environment across much of the world. However, as new materials are developed and new pressures come to bear, revisions to monitoring programmes will be required. In the last 20 years acid rain, synthetic hormone analogues, halogenated hydrocarbons, greenhouse gases and many others have required changes to monitoring strategies.

Biological

In ecological monitoring, the monitoring strategy and effort is directed at the plants and animals in the environment under review and is specific to each individual study.

However, in more generalised environmental monitoring, many animals act as robust indicators of the quality of the environment that they are experiencing or have experienced in the recent past. One of the most familiar examples is the monitoring of numbers of Salmonid fish such as brown trout or Atlantic salmon in river systems and lakes to detect slow trends in adverse environmental effects. The steep decline in salmonid fish populations was one of the early indications of the problem that later became known as acid rain.

In recent years much more attention has been given to a more holistic approach in which the ecosystem health is assessed and used as the monitoring tool itself. It is this approach that underpins the monitoring protocols of the Water Framework Directive in the European Union.

Radiological

Radiation monitoring involves the measurement of radiation dose or radionuclide contamination for reasons related to the assessment or control of exposure to ionizing radiation or radioactive substances, and the interpretation of the results. The ‘measurement’ of dose often means the measurement of a dose equivalent quantity as a proxy (i.e. substitute) for a dose quantity that cannot be measured directly. Also, sampling may be involved as a preliminary step to measurement of the content of radionuclides in environmental media. The methodological and technical details of the design and operation of monitoring programmes and systems for different radionuclides, environmental media and types of facility are given in IAEA Safety Guide RS–G-1.8 and in IAEA Safety Report No. 64.

Radiation monitoring is often carried out using networks of fixed and deployable sensors such as the US Environmental Protection Agency's Radnet and the SPEEDI network in Japan. Airborne surveys are also made by organizations like the Nuclear Emergency Support Team

Microbiological

Bacteria and viruses are the most commonly monitored groups of microbiological organisms and even these are only of great relevance where water in the aquatic environment is subsequently used as drinking water or where water contact recreation such as swimming or canoeing is practised.

Although pathogens are the primary focus of attention, the principal monitoring effort is almost always directed at much more common indicator species such as Escherichia coli, supplemented by overall coliform bacteria counts. The rationale behind this monitoring strategy is that most human pathogens originate from other humans via the sewage stream. Many sewage treatment plants have no sterilisation final stage and therefore discharge an effluent which, although having a clean appearance, still contains many millions of bacteria per litre, the majority of which are relatively harmless coliform bacteria. Counting the number of harmless (or less harmful) sewage bacteria allows a judgement to be made about the probability of significant numbers of pathogenic bacteria or viruses being present. Where E. coli or coliform levels exceed pre-set trigger values, more intensive monitoring including specific monitoring for pathogenic species is then initiated.

Populations

Monitoring strategies can produce misleading answers when relaying on counts of species or presence or absence of particular organisms if there is no regard to population size. Understanding the populations dynamics of an organism being monitored is critical.

As an example if presence or absence of a particular organism within a 10 km square is the measure adopted by a monitoring strategy, then a reduction of population from 10,000 per square to 10 per square will go unnoticed despite the very significant impact experienced by the organism.

Monitoring programmes

All scientifically reliable environmental monitoring is performed in line with a published programme. The programme may include the overall objectives of the organisation, references to the specific strategies that helps deliver the objective and details of specific projects or tasks within those strategies the key feature of any programme is the listing of what is being monitored and how that monitoring is to take place and the time-scale over which it should all happen. Typically, and often as an appendix, a monitoring programme will provide a table of locations, dates and sampling methods that are proposed and which, if undertaken in full, will deliver the published monitoring programme.

There are a number of commercial software packages which can assist with the implementation of the programme, monitor its progress and flag up inconsistencies or omissions but none of these can provide the key building block which is the programme itself.

Environmental monitoring data management systems

Given the multiple types and increasing volumes and importance of monitoring data, commercial software Environmental Data Management Systems (EDMS) or E-MDMS are increasingly in common use by regulated industries. They provide a means of managing all monitoring data in a single central place. Quality validation, compliance checking, verifying all data has been received, and sending alerts are generally automated. Typical interrogation functionality enables comparison of data sets both temporarily and spatially. They will also generate regulatory and other reports. 

One formal certification scheme exists specifically for environmental data management software. This is provided by the Environment Agency in the U.K. under its Monitoring Certification Scheme (MCERTS).

Sampling methods

There are a wide range of sampling methods which depend on the type of environment, the material being sampled and the subsequent analysis of the sample. 

At its simplest a sample can be filling a clean bottle with river water and submitting it for conventional chemical analysis. At the more complex end, sample data may be produced by complex electronic sensing devices taking sub-samples over fixed or variable time periods. 

Judgmental sampling

In judgmental sampling, the selection of sampling units (i.e., the number and location and/or timing of collecting samples) is based on knowledge of the feature or condition under investigation and on professional judgment. Judgmental sampling is distinguished from probability-based sampling in that inferences are based on professional judgment, not statistical scientific theory. Therefore, conclusions about the target population are limited and depend entirely on the validity and accuracy of professional judgment; probabilistic statements about parameters are not possible. As described in subsequent chapters, expert judgment may also be used in conjunction with other sampling designs to produce effective sampling for defensible decisions.

Simple random sampling

In simple random sampling, particular sampling units (for example, locations and/or times) are selected using random numbers, and all possible selections of a given number of units are equally likely. For example, a simple random sample of a set of drums can be taken by numbering all the drums and randomly selecting numbers from that list or by sampling an area by using pairs of random coordinates. This method is easy to understand, and the equations for determining sample size are relatively straightforward. An example is shown in Figure 2-2. This figure illustrates a possible simple random sample for a square area of soil. Simple random sampling is most useful when the population of interest is relatively homogeneous; i.e., no major patterns of contamination or “hot spots” are expected. The main advantages of this design are:
  1. It provides statistically unbiased estimates of the mean, proportions, and variability.
  2. It is easy to understand and easy to implement.
  3. Sample size calculations and data analysis are very straightforward.
In some cases, implementation of a simple random sample can be more difficult than some other types of designs (for example, grid samples) because of the difficulty of precisely identifying random geographic locations. Additionally, simple random sampling can be more costly than other plans if difficulties in obtaining samples due to location causes an expenditure of extra effort.

Stratified sampling

In stratified sampling, the target population is separated into non-overlapping strata, or subpopulations that are known or thought to be more homogeneous (relative to the environmental medium or the contaminant), so that there tends to be less variation among sampling units in the same stratum than among sampling units in different strata. Strata may be chosen on the basis of spatial or temporal proximity of the units, or on the basis of preexisting information or professional judgment about the site or process. Advantages of this sampling design are that it has potential for achieving greater precision in estimates of the mean and variance, and that it allows computation of reliable estimates for population subgroups of special interest. Greater precision can be obtained if the measurement of interest is strongly correlated with the variable used to make the strata.

Systematic and grid sampling

In systematic and grid sampling, samples are taken at regularly spaced intervals over space or time. An initial location or time is chosen at random, and then the remaining sampling locations are defined so that all locations are at regular intervals over an area (grid) or time (systematic). Examples Systematic Grid Sampling - Square Grid Systematic Grid Sampling - Triangular Grids of systematic grids include square, rectangular, triangular, or radial grids. Cressie, 1993. In random systematic sampling, an initial sampling location (or time) is chosen at random and the remaining sampling sites are specified so that they are located according to a regular pattern. Random systematic sampling is used to search for hot spots and to infer means, percentiles, or other parameters and is also useful for estimating spatial patterns or trends over time. This design provides a practical and easy method for designating sample locations and ensures uniform coverage of a site, unit, or process.

Ranked set sampling is an innovative design that can be highly useful and cost efficient in obtaining better estimates of mean concentration levels in soil and other environmental media by explicitly incorporating the professional judgment of a field investigator or a field screening measurement method to pick specific sampling locations in the field. Ranked set sampling uses a two-phase sampling design that identifies sets of field locations, utilizes inexpensive measurements to rank locations within each set, and then selects one location from each set for sampling. In ranked set sampling, m sets (each of size r) of field locations are identified using simple random sampling. The locations are ranked independently within each set using professional judgment or inexpensive, fast, or surrogate measurements. One sampling unit from each set is then selected (based on the observed ranks) for subsequent measurement using a more accurate and reliable (hence, more expensive) method for the contaminant of interest. Relative to simple random sampling, this design results in more representative samples and so leads to more precise estimates of the population parameters. Ranked set sampling is useful when the cost of locating and ranking locations in the field is low compared to laboratory measurements. It is also appropriate when an inexpensive auxiliary variable (based on expert knowledge or measurement) is available to rank population units with respect to the variable of interest. To use this design effectively, it is important that the ranking method and analytical method are strongly correlated.

Adaptive cluster sampling

In adaptive cluster sampling, samples are taken using simple random sampling, and additional samples are taken at locations where measurements exceed some threshold value. Several additional rounds of sampling and analysis may be needed. Adaptive cluster sampling tracks the selection probabilities for later phases of sampling so that an unbiased estimate of the population mean can be calculated despite oversampling of certain areas. An example application of adaptive cluster sampling is delineating the borders of a plume of contamination. Adaptive sampling is useful for estimating or searching for rare characteristics in a population and is appropriate for inexpensive, rapid measurements. It enables delineating the boundaries of hot spots, while also using all data collected with appropriate weighting to give unbiased estimates of the population mean.

Grab samples

Collecting a grab sample on a stream
 
Grab samples are samples taken of a homogeneous material, usually water, in a single vessel. Filling a clean bottle with river water is a very common example. Grab samples provide a good snap-shot view of the quality of the sampled environment at the point of sampling and at the time of sampling. Without additional monitoring, the results cannot be extrapolated to other times or to other parts of the river, lake or ground-water.

In order to enable grab samples or rivers to be treated as representative, repeat transverse and longitudinal transect surveys taken at different times of day and times of year are required to establish that the grab-sample location is as representative as is reasonably possible. For large rivers such surveys should also have regard to the depth of the sample and how to best manage the sampling locations at times of flood and drought.

A rosette sampler used for ocean monitoring
 
In lakes grab samples are relatively simple to take using depth samplers which can be lowered to a pre-determined depth and then closed trapping a fixed volume of water from the required depth. In all but the shallowest lakes, there are major changes in the chemical composition of lake water at different depths, especially during the summer months when many lakes stratify into a warm, well oxygenated upper layer (epilimnion) and a cool de-oxygenated lower layer (hypolimnion).

In the open seas marine environment grab samples can establish a wide range of base-line parameters such as salinity and a range of cation and anion concentrations. However, where changing conditions are an issue such as near river or sewage discharges, close to the effects of volcanism or close to areas of freshwater input from melting ice, a grab sample can only give a very partial answer when taken on its own. 

Semi-continuous monitoring and continuous

An automated sampling station and data logger (to record temperature, specific conductance, and dissolved oxygen levels)
 
There is a wide range of specialized sampling equipment available that can be programmed to take samples at fixed or variable time intervals or in response to an external trigger. For example, a sampler can be programmed to start taking samples of a river at 8-minute intervals when the rainfall intensity rises above 1 mm / hour. The trigger in this case may be a remote rain gauge communicating with the sampler by using cell phone or meteor burst technology. Samplers can also take individual discrete samples at each sampling occasion or bulk up samples into composite so that in the course of one day, such a sampler might produce 12 composite samples each composed of 6 sub-samples taken at 20-minute intervals. 

Continuous or quasi-continuous monitoring involves having an automated analytical facility close to the environment being monitored so that results can, if required, be viewed in real time. Such systems are often established to protect important water supplies such as in the River Dee regulation system but may also be part of an overall monitoring strategy on large strategic rivers where early warning of potential problems is essential. Such systems routinely provide data on parameters such as pH, dissolved oxygen, conductivity, turbidity and colour but it is also possible to operate gas liquid chromatography with mass spectrometry technologies (GLC/MS) to examine a wide range of potential organic pollutants. In all examples of automated bank-side analysis there is a requirement for water to be pumped from the river into the monitoring station. Choosing a location for the pump inlet is equally as critical as deciding on the location for a river grab sample. The design of the pump and pipework also requires careful design to avoid artefacts being introduced through the action of pumping the water. Dissolved oxygen concentration is difficult to sustain through a pumped system and GLC/MS facilities can detect micro-organic contaminants from the pipework and glands

Passive sampling

The use of passive samplers greatly reduces the cost and the need of infrastructure on the sampling location. Passive samplers are semi-disposable and can be produced at a relatively low cost, thus they can be employed in great numbers, allowing for a better cover and more data being collected. Due to being small the passive sampler can also be hidden, and thereby lower the risk of vandalism. Examples of passive sampling devices are the diffusive gradients in thin films (DGT) sampler, Chemcatcher, Polar organic chemical integrative sampler (POCIS), semipermeable membrane devices (SPMDs), stabilized liquid membrane devices (SLMDs), and an air sampling pump.

Remote surveillance

Although on-site data collection using electronic measuring equipment is common-place, many monitoring programmes also use remote surveillance and remote access to data in real time. This requires the on-site monitoring equipment to be connected to a base station via either a telemetry network, land-line, cell phone network or other telemetry system such as Meteor burst. The advantage of remote surveillance is that many data feeds can come into a single base station for storing and analysis. It also enable trigger levels or alert levels to be set for individual monitoring sites and/or parameters so that immediate action can be initiated if a trigger level is exceeded. The use of remote surveillance also allows for the installation of very discrete monitoring equipment which can often be buried, camouflaged or tethered at depth in a lake or river with only a short whip aerial protruding. Use of such equipment tends to reduce vandalism and theft when monitoring in locations easily accessible by the public. 

Remote sensing

Environmental remote sensing uses aircraft or satellites to monitor the environment using multi-channel sensors.

There are two kinds of remote sensing. Passive sensors detect natural radiation that is emitted or reflected by the object or surrounding area being observed. Reflected sunlight is the most common source of radiation measured by passive sensors and in environmental remote sensing, the sensors used are tuned to specific wavelengths from far infrared through visible light frequencies to the far ultraviolet. The volumes of data that can be collected are very large and require dedicated computational support. The output of data analysis from remote sensing are false colour images which differentiate small differences in the radiation characteristics of the environment being monitored. With a skilful operator choosing specific channels it is possible to amplify differences which are imperceptible to the human eye. In particular it is possible to discriminate subtle changes in chlorophyll a and chlorophyll b concentrations in plants and show areas of an environment with slightly different nutrient regimes. 

Active remote sensing emits energy and uses a passive sensor to detect and measure the radiation that is reflected or backscattered from the target. LIDAR is often used to acquire information about the topography of an area, especially when the area is large and manual surveying would be prohibitively expensive or difficult. 

Remote sensing makes it possible to collect data on dangerous or inaccessible areas. Remote sensing applications include monitoring deforestation in areas such as the Amazon Basin, the effects of climate change on glaciers and Arctic and Antarctic regions, and depth sounding of coastal and ocean depths. 

Orbital platforms collect and transmit data from different parts of the electromagnetic spectrum, which in conjunction with larger scale aerial or ground-based sensing and analysis, provides information to monitor trends such as El Niño and other natural long and short term phenomena. Other uses include different areas of the earth sciences such as natural resource management, land use planning and conservation.

Bio-monitoring

The use of living organisms as monitoring tools has many advantages. Organisms living in the environment under study are constantly exposed to the physical, biological and chemical influences of that environment. Organisms that have a tendency to accumulate chemical species can often accumulate significant quantities of material from very low concentrations in the environment. Mosses have been used by many investigators to monitor heavy metal concentrations because of their tendency to selectively adsorb heavy metals.

Similarly, eels have been used to study halogenated organic chemicals, as these are adsorbed into the fatty deposits within the eel.

Other sampling methods

Ecological sampling requires careful planning to be representative and as noninvasive as possible. For grasslands and other low growing habitats the use of a quadrat – a 1-metre square frame – is often used with the numbers and types of organisms growing within each quadrat area counted.

Sediments and soils require specialist sampling tools to ensure that the material recovered is representative. Such samplers are frequently designed to recover a specified volume of material and may also be designed to recover the sediment or soil living biota as well such as the Ekman grab sampler. 

Data interpretations

The interpretation of environmental data produced from a well designed monitoring programme is a large and complex topic addressed by many publications. Regrettably it is sometimes the case that scientists approach the analysis of results with a pre-conceived outcome in mind and use or misuse statistics to demonstrate that their own particular point of view is correct.

Statistics remains a tool that is equally easy to use or to misuse to demonstrate the lessons learnt from environmental monitoring. 

Environmental quality indices

Since the start of science-based environmental monitoring, a number of quality indices have been devised to help classify and clarify the meaning of the considerable volumes of data involved. Stating that a river stretch is in "Class B" is likely to be much more informative than stating that this river stretch has a mean BOD of 4.2, a mean dissolved oxygen of 85%, etc. In the UK the Environment Agency formally employed a system called General Quality Assessment (GQA) which classified rivers into six quality letter bands from A to F based on chemical criteria and on biological criteria. The Environment Agency and its devolved partners in Wales (Countryside Council for Wales, CCW) and Scotland (Scottish Environmental Protection Agency, SEPA) now employ a system of biological, chemical and physical classification for rivers and lakes that corresponds with the EU Water Framework Directive.

Inequality (mathematics)

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Inequality...