Environmental health

environmental health

academic discipline, field of study, field of study, academic major

Subclass of	public health
Facet give	public health
Studied by	environmental health sciences

Conceptual map wey dey show how nature, ecosystem services, environmental ethics, environmental justice, and public health connect together.

Environmental health indicator (2016). E get three main categories: health impacts, air quality, and water plus sanitation. The health impacts category include the environmental risk exposure indicator.

Environmental health be branch of public health wey dey focus on all de things for de natural environment wey dem build environment wey fit affect human health. De study dey help identify wetin be de requirements for healthy environment, so dat people fit control de factors wey dey affect health insyd an effective way. De main sub-disciplines for environmental health be environmental science, toxicology, environmental epidemiology, environmental medicine, den occupational medicine.

Definitions

WHO definitions

World Health Organization (WHO) define environmental health for one document wey dem publish for 1989 as: Those aspects of human health and disease that are determined by factors in the environment. Dem still describe am as de theory plus practice of assessing den controlling de factors for de environment wey fit affect people dema health.

As of 2016, the WHO website about environmental health talk say: Environmental health dey cover all the physical, chemical, and biological factors outside a person, plus all the related factors wey fit affect human behaviour. E include the assessment and control of those environmental factors wey fit affect health. The main aim be to prevent diseases and create environments wey support good health. This definition no include behaviours wey no relate to the environment, behaviours wey relate to the social and cultural environment, or genetics.

Environmental health still dey check how exposure to things like air pollution, contaminated water, and chemicals fit affect people's health as time dey go.

Other considerations

People fit also see the term environmental medicine as one medical specialty, or as one branch under the broader field of environmental health. People never fully agree on the terminology, and for plenty European countries, dem dey use both terms to mean the same thing.

Other terms wey people dey use for, or wey closely relate to, environmental health include environmental public health and health protection.

Disciplines

Five main disciplines dey normally contribute to the field of environmental health, though some of dem dey overlap:

• Environmental epidemiology dey study the relationship between environmental exposures (including exposure to chemicals, radiation, microbiological agents, and others) and human health. Observational studies, wey simply observe exposures wey people don already experience, be very common for environmental epidemiology because e no dey ethical to deliberately expose human beings to agents wey people know or suspect say e fit cause disease. Even though researchers no fit use experimental study designs be one limitation, this discipline dey observe the effects directly on human health instead of estimating the effects from animal studies. Environmental epidemiology na the study of how physical, biological, and chemical factors for the external environment dey affect human health. E still dey examine specific populations or communities wey different environmental conditions expose to understand the relationship between physical, biological, or chemical factors and human health.
• Toxicology dey study how exposure to things for the environment fit lead to specific health problems, mostly by using animals so researchers fit understand the possible effects on human health. Toxicology get advantage because researchers fit carry out randomized controlled trials and other experimental studies with animal subjects. But plenty differences still dey between animal biology and human biology, so people need to take care when dem dey interpret results from animal studies for human health.

• Exposure science dey study how human beings dey come into contact with environmental contaminants by identifying and measuring the level of exposure. Exposure science fit support environmental epidemiology by giving a clearer description of environmental exposures wey fit lead to a particular health outcome. E fit also identify common exposures wey toxicology studies fit investigate further, or support risk assessments to determine whether current exposure levels pass the recommended limits. One major advantage of exposure science be say e fit measure exposure to specific chemicals very accurately. However, e no provide direct information about health outcomes like environmental epidemiology or toxicology.

• Environmental engineering dey apply scientific and engineering principles to protect people from the harmful effects of environmental factors, protect the environment from the harmful effects of both natural and human activities, and improve the overall quality of the environment.

• Environmental law include the network of treaties, statutes, regulations, common laws, and customary laws wey address the effects of human activities on the natural environment.

Information from epidemiology, toxicology, and exposure science fit combine together to carry out risk assessment for specific chemicals, mixtures of chemicals, or other risk factors, so researchers fit determine whether a particular exposure dey pose serious risk to human health (meaning the exposure fit likely cause pollution-related diseases). The results fit help develop and implement environmental health policies, for example, policies wey regulate chemical emissions or set standards for proper sanitation.

Engineering and legal intervention strategies fit also work together to monitor and manage exposure risks, with the main aim of protecting human health.

Pediatric environmental health

Children's environmental health na academic discipline wey dey study how environmental exposures for early life—including chemical, biological, nutritional, and social exposures—dey affect children's health and development, and even their health throughout the whole human life span.

Pediatric environmental health base on the understanding say children no be "small adults." Babies and children get their own unique ways of exposure and special vulnerabilities. The environmental risks wey babies and children face differ from those of adults both in quality and quantity. Pediatric environmental health be highly interdisciplinary. E dey bring together general pediatrics, many pediatric subspecialties, epidemiology, occupational medicine, environmental medicine, medical toxicology, industrial hygiene, and exposure science.

Concerns

Overview of the main health effects of some common types of pollution on human beings.

FEMA/EPA Hazardous Materials Team dey remove hazardous materials wey Hurricane Katrina leave behind for 2005.

Lecture by Joyeeta Gupta (University of Amsterdam) about environmental health.

Environmental health concerns include:

• Biosafety.
• Disaster preparedness and response.
• Food safety, including agriculture, transportation, food processing, wholesale, and retail distribution and sales.
• Housing, including the control of substandard housing and inspection of jails and prisons.
• Prevention of childhood lead poisoning.
• Land use planning, including smart growth.
• Disposal of liquid waste, including municipal wastewater treatment plants and on-site wastewater disposal systems such as septic tanks and chemical toilets.
• Management and disposal of medical waste.
• Occupational health and industrial hygiene.
• Radiological health, including exposure to ionizing radiation from X-rays or radioactive isotopes.
• Prevention of recreational water illnesses from swimming pools, spas, oceans, rivers, lakes, and other freshwater bathing places.
• Solid waste management, including landfills, recycling facilities, composting, and solid waste transfer stations.
• Exposure to toxic chemicals from consumer products, homes, workplaces, air, water, or soil.
• Toxins from molds and algal blooms.
• Vector control, including the control of mosquitoes, rodents, flies, cockroaches, and other animals wey fit spread pathogens.

According to recent estimates for Europe, about 5% to 10% of disability-adjusted life years (DALYs) wey people lose dey happen because of environmental causes. The biggest contributor by far be fine particulate matter pollution for urban air. Likewise, researchers estimate say environmental exposures contribute to 4.9 million (8.7%) deaths and 86 million (5.7%) DALYs globally.

For the United States, Superfund sites wey different companies create don prove say dem dey dangerous to both human health and the environment for nearby communities. Na this perceived threat—especially the fear of miscarriages, mutations, birth defects, and cancers—wey make the public worry pass.

Air quality

Air quality include both outdoor (ambient) air quality and indoor air quality. Some of the biggest concerns about air quality include environmental tobacco smoke, air pollution from different kinds of chemical waste, and other forms of air pollution wey fit affect human health.

Outdoor air quality

Air pollution dey cause more than 6.5 million deaths worldwide every year, As of 2022. Air pollution be major risk factor for diseases like lung cancer, respiratory infections, asthma, heart disease, and many other respiratory illnesses. When air pollution reduce, adult mortality too dey reduce, which means improving air quality fit save plenty lives.

Factory for Mumbai dey release air pollution.

Some of the common sources of emissions include road traffic, energy production, household fuel burning, aviation, motor vehicles, and other pollution sources. These activities involve burning fuel, which dey release harmful particles into the air. Humans and other living organisms fit breathe in or swallow these particles.

Air pollution dey linked with serious health problems such as respiratory diseases, cardiovascular diseases, cancer, and even death.

The risk wey air pollution pose depend on how dangerous the pollutant be and how much exposure the person get. For example, one child wey dey play sports outside every day get higher chance of exposure to outdoor air pollution than one adult wey spend most of the time inside office or house.

Environmental health officials dey work to identify people wey get high risk of exposure to air pollution, identify the risk factors wey dey communities, and help reduce the overall exposure of the whole community.

Indoor air quality

Indoor air quality (IAQ) is an important aspect of smart water systems in Africa because water supply and treatment facilities can influence the quality of air inside buildings. Poorly maintained water systems may promote the growth of mould, bacteria, and other microorganisms, which can release pollutants into indoor environments. Smart water technologies help monitor water quality, humidity, leaks, and ventilation conditions, reducing health risks associated with contaminated indoor air.

Smart sensors installed in buildings can detect leaks, excessive moisture, and water stagnation, allowing facility managers to respond quickly before mould develops. In hospitals, schools, offices, and residential buildings, these systems contribute to healthier indoor environments by preventing water-related air pollution.

Water treatment facilities also use digital monitoring systems to ensure that chemicals such as chlorine are applied at safe levels. Automated ventilation systems integrated with smart building technologies help remove airborne contaminants generated during water treatment processes.

Several African countries are adopting smart building management systems that combine water monitoring with heating, ventilation, and air conditioning (HVAC) controls. These integrated systems improve energy efficiency while maintaining healthy indoor conditions.

Although adoption remains limited due to infrastructure and financial constraints, growing investments in smart cities and green buildings are increasing the use of intelligent water and environmental monitoring systems across Africa.

Benefits

• Reduces mould growth caused by water leaks and dampness.
• Improves occupant health by maintaining cleaner indoor air.
• Enables early detection of plumbing failures and water contamination.
• Supports energy-efficient building management.
• Reduces maintenance costs through predictive monitoring.

Challenges

• High installation and maintenance costs.
• Limited technical expertise in integrated building management systems.
• Inadequate digital infrastructure in many regions.
• Lack of standards for smart indoor environmental monitoring.
• Limited awareness among building owners and facility managers.

Climate change adaptation

Smart water systems play an increasingly important role in helping African countries adapt to the effects of climate change. Rising temperatures, changing rainfall patterns, prolonged droughts, floods, and increasing water scarcity have placed significant pressure on water resources across the continent. Digital technologies enable water managers to monitor these changes in real time and respond more effectively.

Remote sensors, satellite imagery, weather forecasting, and Geographic Information Systems (GIS) are used to monitor rainfall, river flows, groundwater levels, reservoir storage, and soil moisture. These data help governments, utilities, and farmers make informed decisions about water allocation, irrigation scheduling, and emergency response during droughts and floods.

Smart irrigation systems reduce water consumption by applying water only when crops require it. Combined with weather forecasts and soil moisture sensors, these systems improve agricultural productivity while conserving limited water resources. In regions frequently affected by drought, such technologies enhance food security and strengthen the resilience of farming communities.

Urban water utilities also use smart monitoring systems to prepare for climate-related disasters. Early warning systems can detect rising river levels, pipeline failures, or abnormal water demand during extreme weather events. Automated control systems allow operators to manage reservoirs, pumping stations, and drainage infrastructure more efficiently, reducing the impacts of flooding and water shortages.

Nature-based solutions are increasingly being integrated with smart water management. Digital monitoring supports the restoration of wetlands, watersheds, forests, and river ecosystems by tracking environmental conditions and evaluating conservation efforts. These approaches improve water quality, groundwater recharge, and biodiversity while strengthening resilience to climate change.

International organizations, research institutions, and development partners continue to support African countries through climate adaptation programmes that promote digital water technologies, capacity building, and sustainable infrastructure. However, widespread implementation remains constrained by limited financial resources, inadequate technical capacity, unreliable electricity, and unequal access to digital technologies.

Adaptation strategies

• Real-time monitoring of water resources.
• Smart irrigation based on weather and soil moisture data.
• Flood forecasting and early warning systems.
• Digital monitoring of reservoirs and groundwater.
• Integration of satellite data and GIS for water planning.
• Nature-based water management supported by environmental monitoring.

Benefits

• Improves resilience to droughts and floods.
• Enhances food security through efficient irrigation.
• Supports sustainable water resource management.
• Reduces disaster risks through early warning systems.
• Improves long-term planning under changing climate conditions.

Water governance and policy

Effective water governance is essential for the successful implementation of smart water systems in Africa. Water governance refers to the processes, institutions, laws, and policies used to manage water resources and provide reliable water services. Smart water technologies support better governance by improving data collection, transparency, accountability, and decision-making.

Traditional water management systems in many African countries often face challenges such as limited access to accurate data, weak monitoring systems, ageing infrastructure, and difficulties in coordinating between different institutions. Smart water systems address these challenges by providing real-time information about water availability, consumption patterns, infrastructure performance, and service delivery.

Digital platforms allow water authorities to collect and analyse large amounts of data from sensors, meters, satellites, and customer systems. This information helps policymakers develop evidence-based strategies for water allocation, conservation, and infrastructure development. Open data initiatives can also improve public participation by allowing communities, researchers, and organizations to access water-related information.

Smart water technologies contribute to improved accountability among water service providers. Automated metering systems reduce billing errors, detect illegal connections, and improve revenue collection. Leak detection technologies help utilities reduce non-revenue water, which is a major challenge affecting many African water providers.

Government policies and regulatory frameworks play a key role in encouraging smart water adoption. Countries that establish clear standards for digital infrastructure, data protection, water quality monitoring, and public-private partnerships are better positioned to benefit from smart water innovations.

Regional organizations such as the African Union and various water management institutions have emphasized the importance of digital transformation and integrated water resource management. Collaboration between governments, technology companies, research institutions, and local communities is necessary to ensure that smart water systems are inclusive and sustainable.

Despite these opportunities, challenges remain, including limited funding, weak institutional capacity, poor coordination between agencies, and concerns about data ownership and cybersecurity. Addressing these issues is important for creating effective and equitable smart water governance systems across Africa.

Governance applications

• Digital water information management platforms.
• Real-time monitoring of water supply networks.
• Automated billing and smart metering systems.
• Data-driven water policy development.
• Public access to water information.
• Improved coordination among water institutions.

Policy requirements

• Development of national smart water strategies.
• Investment in digital infrastructure and skills development.
• Strong regulations for data protection and cybersecurity.
• Support for research and innovation.
• Promotion of partnerships between government and private sectors.

Artificial intelligence and machine learning in smart water systems

Artificial intelligence (AI) and machine learning (ML) are emerging technologies that are transforming smart water systems in Africa. These technologies allow water authorities and utilities to analyse large amounts of data collected from sensors, satellites, smart meters, and monitoring devices to improve water management decisions.

AI-powered systems can identify patterns in water consumption, predict equipment failures, detect leaks, and optimize water distribution networks. By analysing historical and real-time data, machine learning algorithms can forecast water demand, helping utilities manage limited water resources more efficiently.

One major application of AI in smart water management is predictive maintenance. Traditional water infrastructure maintenance often depends on scheduled inspections or responses after failures occur. AI systems can analyse pressure changes, flow rates, and equipment performance to predict possible pipe failures before they happen. This reduces repair costs and prevents service interruptions.

AI technologies are also being used to improve water quality monitoring. Machine learning models can analyse data from water sensors to detect unusual changes in chemical composition, pollution levels, and microbial risks. Early detection allows authorities to take corrective measures before contaminated water reaches consumers.

In agriculture, AI-based smart irrigation systems combine weather data, satellite imagery, and soil information to determine the exact amount of water required by crops. This helps farmers increase productivity while reducing unnecessary water use.

African cities are increasingly exploring AI applications as part of smart city development. Water utilities can integrate artificial intelligence with Internet of Things (IoT) devices, geographic information systems (GIS), and cloud computing platforms to create more responsive and efficient water networks.

However, the adoption of AI in African water systems faces several challenges. These include limited access to high-quality datasets, inadequate digital infrastructure, high technology costs, shortage of AI specialists, and concerns about data privacy. Addressing these barriers requires investment in education, research, digital infrastructure, and collaboration between governments, universities, and technology companies.

Applications of AI in smart water systems

• Predicting water demand and consumption patterns.
• Detecting leaks and abnormal water usage.
• Predictive maintenance of pipelines and equipment.
• Automated water quality monitoring.
• Optimizing irrigation systems.
• Supporting climate change forecasting and planning.

Benefits

• Improves efficiency of water management.
• Reduces operational and maintenance costs.
• Enables faster responses to water problems.
• Supports evidence-based decision-making.
• Enhances conservation of water resources.

Challenges

• Limited availability of reliable water datasets.
• High cost of AI infrastructure.
• Shortage of technical expertise.
• Cybersecurity and data privacy concerns.
• Unequal access to digital technologies.

Internet of Things (IoT) and smart water networks

The Internet of Things (IoT) is one of the key technologies supporting the development of smart water systems in Africa. IoT refers to networks of connected devices that collect, exchange, and analyse data through digital communication systems. In smart water management, IoT devices such as sensors, smart meters, controllers, and monitoring equipment help water providers track and manage water resources more effectively.

IoT-based smart water networks use sensors installed in pipelines, reservoirs, treatment plants, and distribution systems to collect real-time information on water flow, pressure, quality, and consumption. This information is transmitted through communication networks to centralized platforms where it can be analysed and used for decision-making.

One of the most important applications of IoT is leak detection. Water losses from damaged pipes and illegal connections are major challenges for many African water utilities. IoT sensors can identify unusual changes in pressure and flow, allowing maintenance teams to locate and repair leaks quickly. This reduces water waste and improves the reliability of water supply systems.

Smart meters connected through IoT networks provide households and businesses with accurate information about their water consumption. These systems encourage responsible water use by allowing users to monitor their usage patterns and identify unnecessary consumption. For utilities, smart meters improve billing accuracy, reduce operational costs, and increase revenue collection.

IoT technologies are also being used in rural water supply systems. Solar-powered monitoring devices can track the operation of boreholes, pumps, and community water facilities in remote areas. This enables organizations and governments to identify failures quickly and improve access to safe drinking water.

The integration of IoT with artificial intelligence, cloud computing, and geographic information systems creates advanced smart water networks capable of automatic decision-making. These integrated systems can optimize water distribution, predict future demand, and improve emergency responses during droughts or floods.

Despite its advantages, IoT adoption in Africa faces challenges such as limited internet connectivity, unreliable electricity supply, high equipment costs, and lack of technical skills for installation and maintenance. Expanding digital infrastructure and developing local expertise are important steps toward wider adoption of IoT-based water management solutions.

IoT applications in smart water systems

• Real-time monitoring of pipelines and water facilities.
• Smart water metering for households and industries.
• Automated leak detection.
• Remote monitoring of rural water systems.
• Water quality sensing and alerts.
• Intelligent control of pumps and treatment facilities.

Benefits

• Reduces water losses and improves efficiency.
• Provides accurate and timely water data.
• Supports preventive maintenance.
• Improves service delivery in urban and rural areas.
• Enables better resource planning.

Challenges

• Limited network coverage in some regions.
• High costs of IoT devices and connectivity.
• Energy supply challenges in remote locations.
• Need for technical training and maintenance capacity.
• Cybersecurity risks affecting connected systems.

Big data analytics and cloud computing

Big data analytics and cloud computing are important components of modern smart water systems in Africa. These technologies enable water organizations to collect, store, process, and analyse large volumes of information generated from smart meters, sensors, satellites, weather stations, and customer management platforms.

Traditional water management systems often rely on manual data collection and delayed reporting, making it difficult for authorities to respond quickly to water challenges. Big data analytics improves this process by transforming large datasets into useful information that supports planning, monitoring, and decision-making.

Water utilities can use big data analytics to understand consumption patterns, identify areas with high water demand, predict future requirements, and optimize distribution networks. By analysing historical and real-time data, utilities can reduce water losses, improve service reliability, and allocate resources more effectively.

Cloud computing provides digital storage and processing capabilities that allow water institutions to manage large datasets without requiring expensive physical infrastructure. Cloud-based platforms enable remote access to water information, allowing engineers, policymakers, and researchers to collaborate and make decisions from different locations.

In urban areas, cloud-based smart water platforms can integrate information from multiple sources, including water treatment plants, pipelines, weather systems, and customer meters. This creates a comprehensive view of the entire water supply network and helps operators detect problems early.

Big data analytics also supports climate change adaptation by analysing environmental information such as rainfall trends, drought conditions, groundwater levels, and river flows. These insights help governments develop strategies for water conservation and emergency response.

In agriculture, farmers and irrigation managers use data analytics to improve water efficiency. Combining information from soil sensors, satellite images, and weather forecasts allows farmers to apply the right amount of water at the right time, reducing waste and improving crop productivity.

However, the use of big data and cloud computing in Africa faces challenges including limited internet connectivity, high costs of digital services, shortage of data science expertise, and concerns about data security and ownership. Strengthening digital infrastructure and developing technical skills are necessary to maximize the benefits of these technologies.

Applications of big data analytics

• Monitoring water consumption trends.
• Predicting water demand.
• Identifying leaks and infrastructure failures.
• Analysing climate and environmental data.
• Supporting water policy and planning.
• Improving agricultural water management.

Applications of cloud computing

• Centralized storage of water data.
• Remote access to monitoring platforms.
• Data sharing between institutions.
• Integration of multiple smart water technologies.
• Supporting artificial intelligence and machine learning systems.

Benefits

• Faster and more accurate decision-making.
• Improved water resource planning.
• Reduced operational costs.
• Better coordination among stakeholders.
• Enhanced ability to respond to climate challenges.

Challenges

• Poor internet infrastructure in some areas.
• Data privacy and cybersecurity risks.
• Limited technical expertise.
• High costs of digital transformation.
• Unequal access to advanced technologies.

Geographic Information Systems (GIS) and remote sensing

Geographic Information Systems (GIS) and remote sensing are important technologies used in smart water systems across Africa. These technologies allow water managers to collect, analyse, visualize, and interpret information about water resources and infrastructure based on geographic locations.

GIS combines digital maps with data from different sources, including water networks, population information, land use patterns, rainfall records, and environmental conditions. In smart water management, GIS helps authorities understand the location and condition of water infrastructure such as pipelines, boreholes, reservoirs, treatment plants, and distribution networks.

Water utilities use GIS to improve infrastructure planning and maintenance. By mapping pipelines and monitoring their performance, utilities can identify areas with frequent breakdowns, prioritize repairs, and plan future expansion. This is particularly useful in rapidly growing African cities where demand for water services continues to increase.

Remote sensing uses satellite images and aerial observations to monitor water resources over large areas. Satellites can provide information about surface water bodies, groundwater conditions, rainfall patterns, vegetation changes, and drought impacts. This makes remote sensing valuable for managing water resources in regions where ground-based monitoring is limited.

In agriculture, GIS and remote sensing support precision irrigation by helping farmers identify crop conditions, soil moisture levels, and areas affected by water stress. These technologies reduce unnecessary water use and improve agricultural productivity.

GIS-based systems are also used for disaster management. During floods, satellite data and geographic analysis help authorities identify vulnerable communities, monitor flood extent, and coordinate emergency responses. During droughts, these tools support the assessment of water availability and the planning of conservation measures.

The combination of GIS, remote sensing, IoT sensors, and artificial intelligence creates powerful decision-support systems for smart water management. These integrated platforms allow governments and organizations to monitor water resources more accurately and develop sustainable solutions.

Despite their benefits, the adoption of GIS and remote sensing technologies in Africa faces challenges such as limited access to high-resolution data, shortage of trained specialists, high costs of equipment and software, and inadequate institutional capacity. Investments in training, open data systems, and affordable digital tools are important for expanding their use.

Applications of GIS in smart water systems

• Mapping water supply infrastructure.
• Planning water distribution networks.
• Monitoring pipeline conditions.
• Supporting urban water planning.
• Identifying areas with poor water access.
• Managing water-related emergencies.

Applications of remote sensing

• Monitoring rivers, lakes, and reservoirs.
• Measuring drought and flood impacts.
• Estimating rainfall and soil moisture.
• Supporting groundwater assessment.
• Monitoring agricultural water needs.
• Tracking environmental changes.

Benefits

• Improves water resource mapping and planning.
• Supports evidence-based decision-making.
• Enables monitoring of large and remote areas.
• Reduces costs of field surveys.
• Strengthens climate change adaptation.

Challenges

• Limited technical expertise.
• Cost of specialized equipment and software.
• Poor availability of local datasets.
• Limited institutional capacity.
• Difficulties integrating different data sources.

External links

• NIEHS