Envirofacts integrates information from a variety of EPA's environmental databases. Each of these databases contains information about facilities that are required to report activity to a state or federal system. Using this API, you can retrieve information.

Our analysis leverages data sourced from publicly available, audited information. We provide environmental and social impact data related to the UN Sustainable Development Goals for every publicly listed company alongside some private companies, with a breakdown of contribution towards all 17 SDGs for benchmarking for sustainability risk. We provide company and portfolio level data, with SDG alignment charts available for publication/marketing purposes.

This methodology has been shown to outperform other ESG data providers, as reported by TGM. It has been shown to be material for forward-looking risk and return, and independently shown to outperform other ESG data providers for ratings impacting on financial performance.

UN SDG Contribution Methodology: Environmental Impact Contribution – Measured as the proportion of SDG contribution that makes a positive impact on the environment. Social Impact Contribution – Measured as the proportion of SDG that makes a positive impact on the well-being of people and society, where the value is a proportion of a company’s revenue in % or $.

Past Use Cases: Acacia Money – SDG benchmarking for sustainability risk Fund manager climate alignment reporting EU Taxonomy alignment

The data set is a collection of environmental records associated with the individual events. The data set has been generated using the serdif-api wrapper (https://github.com/navarral/serdif-api) when sending a CSV file with example events for the Republic of Ireland. The serdif-api send a semantic query that (i) selects the environmental data sets within the region of the event, (ii) filters by the specific period of interest from the event, (iii) aggregates the data sets using the minimum, maximum, average or sum for each of the available variables for a specific time unit. The aggregation method and the time unit can be passed to the serdif-api through the Command Line Interface (CLI) (see example in https://github.com/navarral/serdif-api). The resulting data set format can be also specified as data table (CSV) or as graph (RDF) for analysis and publication as FAIR data. The open-ready data for research is retrieved as a zip file that contains: (i) data as csv: environmental data associated to particular events as a data table (ii) data as rdf: environmental data associated to particular events as a graph (iii) metadata for publication as rdf: metadata record with generalized information about the data that do not contain personal data as a graph; therefore, publishable. (iv) metadata for research as rdf: metadata records with detailed information about the data, such as individual dates, regions, data sets used and data lineage; which could lead to data privacy issues if published without approval from the Data Protection Officer (DPO) and data controller.

A REST web service API allowing the retrieval of historical air quality data from EPA.

This is an api that provides continuous real time as well as historic data from the network of air quality monitoring stations that are part of the national air quality monitoring network managed in cooperation between the Environmental Protection Agency and Dublin City Council, as well as other stations set up by Dublin City Council to monitor local air quality conditions. This api also provides access to Dublin City Council's network of environmental sound level monitors. For more information, visit https://dublincityairandnoise.ie/

SILO (Scientific Information for Land Owners) is a database of Australian climate data from 1889 (current to yesterday). It provides daily datasets for a range of climate variables in ready-to-use formats suitable for research and climate applications. SILO products provide national coverage with interpolated infills for missing data, which allows you to focus on your research or model development without the burden of data preparation.
The SILO climate API (Application Programming Interface) allows you to query point datasets, as well as a range of metadata, in real time.
Note: An API key is required to use this API. Please visit the SILO website to obtain your API key.

FinTech Climate Data API Market Outlook

According to our latest research, the global FinTech Climate Data API market size reached USD 1.34 billion in 2024, and it is expected to grow at a robust CAGR of 24.6% from 2025 to 2033. By 2033, the market is forecasted to reach a substantial USD 11.16 billion. The primary growth factor fueling this market is the increasing regulatory pressure on financial institutions to incorporate climate risk data into their decision-making processes, coupled with rising investor demand for transparency in environmental, social, and governance (ESG) factors.

The surge in demand for climate data APIs within the FinTech sector is closely linked to the global shift toward sustainable finance and responsible investing. Financial institutions, including banks, asset managers, and insurance companies, are under mounting pressure to assess and disclose climate-related risks in their portfolios. This has led to a significant uptick in the adoption of advanced API solutions that seamlessly integrate climate data into existing risk management, investment analysis, and reporting workflows. The ability to access real-time, granular climate data through APIs empowers financial organizations to make informed, data-driven decisions, ensuring compliance with evolving regulatory standards and catering to the growing expectations of stakeholders and investors.

Another major growth driver for the FinTech Climate Data API market is the proliferation of environmental regulations and disclosure frameworks across key markets such as North America, Europe, and Asia Pacific. Governments and regulatory bodies are mandating more stringent climate risk assessments and reporting requirements, particularly for financial institutions. This regulatory push has accelerated the integration of climate data APIs, enabling organizations to enhance their risk assessment models, streamline ESG reporting, and support sustainable investment strategies. Additionally, the emergence of innovative FinTech startups specializing in climate analytics is fostering competition and driving technological advancements in the market.

Technological advancements in data analytics, artificial intelligence, and cloud computing are also playing a pivotal role in shaping the FinTech Climate Data API market. Modern APIs leverage sophisticated machine learning algorithms to provide predictive insights, scenario analysis, and automated compliance checks. The scalability and flexibility offered by cloud-based deployment models are particularly attractive to FinTech companies and financial institutions seeking to minimize infrastructure costs and accelerate time-to-market for new climate-focused products and services. As the market matures, we anticipate a greater emphasis on interoperability, data standardization, and the development of APIs tailored to specific use cases such as carbon accounting, regulatory compliance, and sustainable investment analysis.

Regionally, North America and Europe currently dominate the FinTech Climate Data API market, accounting for the largest share of global revenue in 2024. This dominance is attributed to the early adoption of ESG frameworks, proactive regulatory initiatives, and the strong presence of leading FinTech innovators. However, the Asia Pacific region is witnessing the fastest growth, driven by increasing climate risk awareness, regulatory developments, and the rapid digitalization of financial services. Latin America and the Middle East & Africa are emerging markets with significant growth potential, supported by rising investments in sustainable finance infrastructure and the expansion of FinTech ecosystems.

Component Analysis

The FinTech Climate Data API market is segmented by component into software and services, with each segment contributing distinctly to the market’s overall growth trajectory. The software segment, encompassing API platforms, data integration tools, and analytics engines, holds the majority share of the market. This is primarily due to the increasing demand for robust, scalable, and customizable API solutions that enable financial institutions to seamlessly incorporate climate data into their workflows. Leading software providers are focusing on enhancing API usability, expanding data coverage, and integrating advanced analytics capabilities, which in turn is driving adoption among banks, asset managers, and FinTech companies. The trend toward open banking and API-first architectures f

This is the Bathing Water Open Data API which has three API datasets: Locations, Measurements and Alerts. Bathing water quality is monitored and assessed to make sure it is safe for swimming during the summer bathing season. Bathing water quality is monitored during the summer bathing season which is between 1 June and 15 September (some local authorities also voluntarily monitor outside of the summer bathing season). This information is populated using the EPA’s CRM Bathing Water information service and the EPA’s central water quality database Aquarius. Local authorities report this information to the EPA via the Bathing Water Information System (BWIS) and Monitoring Data System (MDS) applications on EDEN (Environmental Data Exchange Network). The EPA provides this information to the public via the responsive beaches.ie website.

Gongyi Qize Environmental Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This API accesses data from QLD Government's WildNet database that has been approved for public release. There are a number of functions that retrieve information for species, taxonomy, species lists and reference codes.

The API returns the information available in the WildNet Application

If you are establishing a long-term connection to the API, please email WildNet@detsi.qld.gov.au to be added to the API users email list. This list will be notified when major changes are made to the API.

WildNet information can also be accessed through:

Biomaps provides a map interface to display the WildNet records approved for publication with other spatial layers (such as cadastre, protected areas, vegetation and biodiversity value mapping). A range of WildNet species list reports based on all WildNet records and other environmental reports can be requested for properties and drawn areas etc.

WetlandMaps provides a map interface to display WildNet records approved for publication with other spatial layers (such as wetland mapping).

The Queensland Globe provides a map interface to display WildNet records approved for publication with other spatial layers and themes.

Other WildNet products are made available via the Queensland Government Open Data Portal.

This is an api that provides continuous real time as well as historic data from the network of air quality monitoring stations that are part of the national air quality monitoring network managed in cooperation between the Environmental Protection Agency and Dublin City Council, as well as other stations set up by Dublin City Council to monitor local air quality conditions. This api also provides access to Dublin City Council's network of environmental sound level monitors. For more information, visit https://dublincityairandnoise.ie/

This service provides data implemented from geospatial data for the INSPIRE topic:A georeferenced object for the direct collection and processing of data on objects whose properties (e.g. physical, chemical, biological or other aspects of environmental conditions) are repeatedly observed or measured. An environmental monitoring facility may also accommodate other environmental monitoring facilities.

The World Bank's ESG Data Draft dataset offers insights into 17 crucial sustainability areas, covering environmental, social, and governance aspects.

The Carbon Calculated Platform is a free and open data platform for delivering carbon, energy and environmental calculations to software providers and sustainability professionals

That platform contains standardised data from global sources including governments, universities, NGOs and Energy Star.

It is accessible via an API or online through the browser

[Request an API key now!](http://carboncalculated.com/contacts/new "Request an API key now!)

The Qld Wildlife API is being replaced\r

Please note that the Qld Wildlife API will soon be replaced with a new API. The new API is currently planned to be released in May 2025. Please come back to this webpage for updates. If you have any questions or feedback, please email wildnet@des.qld.gov.au\r

\r This API accesses data from QLD Government's WildNet database that has been approved for public release. There are a number of functions that retrieve species names, profiles, notes, statuses, images, species survey locations and project information. \r \r Please see https://apps.des.qld.gov.au/species for more information on using the API functions. \r \r Data can be retrieved in 3 different formats by adding the format variable to the end of the url (e.g. &f=xml). The default format is json if the f (format) variable is omitted. \r E.g. \r - JSON: https://apps.des.qld.gov.au/species/?op=getkingdomnames&f=json \r - XML: https://apps.des.qld.gov.au/species/?op=getkingdomnames&f=xml \r - CSV: https://apps.des.qld.gov.au/species/?op=getkingdomnames&f=csv \r \r When spatial locations are returned, GeoJSON or KML will be used when requesting the json and xml formats. \r \r Species profile search can be used to locate species information (by name or a taxonomy search). It uses the Get species by ID function to display species profiles with images and maps and uses the Get surveys by species function for downloading data.\r \r Biomaps provides a map interface to display the WildNet records approved for publication with other spatial layers (such as cadastre, protected areas, vegetation and biodiversity value mapping). A range of WildNet species list reports based on all WildNet records and other environmental reports can be requested for properties and drawn areas etc.\r \r WetlandMaps provides a map interface to display WildNet records approved for publication with other spatial layers (such as wetland mapping).\r \r The Queensland Globe can be used to access WildNet records approved release and access summarised WildNet data in 10x10km grids. \r \r Other WildNet products are made available via the Queensland Government Open Data Portal.\r \r The resources listed below are the service endpoints for each of the operations (or functions) available. \r \r Available variables \r f: Format - Setting the 'f' variable will determine the format of the response. There are 4 possible options; json, xml, kml and csv. Json is the default if 'f' is not set. If the output is spatial, GeoJson will be return for 'f=json' and KML will be returned for 'f=xml' or 'f=kml'. \r projids: Project Ids - Comma separated list of project ids. Use Get projects to access project IDs. \r projtitle: Project Title - A title (full or partial) that is used as a search string to search for a project or projects. \r proj: Include Project Details - This indicates if the project details are to be included in the output. The default is true. \r org: Organisation ID - An ID that is associated with an organisation. Use Get organisations to access organisation IDs. \r bbox: Bounding Box - A bounding box that defines a geographical area. Specified as top left, bottom right, e.g. latitude,longitude,latitude,longitude. \r circle: Circle - A circle (buffered point) that defines a geographical area. It is specified as a centroid and a radius (metres), e.g. latitude,longitude,distance. \r pagecount: Page Count - The number of records to return on a page. \r pageindex: Page Index - The page index to return. \r p: Location Precision - The distance in metres that indicates the accuracy of the records location. \r min: Minimum Start Date - The earliest date for a record to be returned. \r max: Maximum Start Date - The latest date for a record to be returned. \r kingdom: Kingdom - A kingdom's common name. \r class: Class - A class scientific name. \r classes: Classes - A comma separated list of class scientific names. \r family: Family - A scientific family name. \r species: Species Name - A scientific species name. \r taxonid: Taxon ID - A unique id that identifies a particular species. Use Species search to access taxonids for particular species.

Carbon Footprint API Gateway Market Outlook

According to our latest research, the global Carbon Footprint API Gateway market size is valued at USD 1.12 billion in 2024 and is expected to reach USD 7.98 billion by 2033, expanding at a robust CAGR of 24.1% during the forecast period. This remarkable growth is primarily fueled by the increasing demand for real-time, automated carbon emissions tracking and sustainability reporting across diverse sectors. Enterprises and governments are accelerating their adoption of digital solutions to meet stringent environmental regulations and achieve net-zero commitments, thereby propelling the market forward.

One of the key growth factors for the Carbon Footprint API Gateway market is the intensifying global focus on sustainability and environmental, social, and governance (ESG) compliance. Organizations worldwide are under mounting pressure to disclose their carbon emissions transparently and accurately, both to satisfy regulatory requirements and to meet the expectations of eco-conscious investors and consumers. This has led to a surge in the deployment of API gateways that enable seamless integration with various data sources and enterprise resource planning (ERP) systems, automating the collection, analysis, and reporting of carbon footprint data. The proliferation of corporate sustainability initiatives and the growing need for granular, real-time emissions data are further accelerating the adoption of these solutions across industries such as energy, manufacturing, and retail.

Furthermore, the rapid advancement of digital technologies such as cloud computing, artificial intelligence, and the Internet of Things (IoT) is significantly enhancing the capabilities of Carbon Footprint API Gateways. Modern API gateways now offer advanced analytics, machine learning-driven insights, and scalable architectures, allowing organizations to process vast volumes of environmental data with high accuracy and efficiency. The integration of carbon footprint APIs with IoT sensors, for example, enables continuous monitoring of emissions from manufacturing plants, logistics fleets, and energy systems. This technological evolution is not only improving data accuracy and operational efficiency but also lowering the barriers to entry for small and medium enterprises, thereby expanding the addressable market.

Additionally, the market is benefiting from a favorable regulatory environment and a growing ecosystem of partnerships between technology providers, environmental organizations, and government agencies. Governments across North America, Europe, and Asia Pacific are enacting stricter carbon reporting mandates and incentivizing the adoption of digital sustainability solutions. This regulatory push, combined with increasing collaboration between public and private sectors, is fostering innovation and driving the development of more robust and interoperable Carbon Footprint API Gateway solutions. As a result, the market is witnessing heightened investment activity and rapid product innovation, further solidifying its long-term growth prospects.

Regionally, North America currently holds the largest share of the Carbon Footprint API Gateway market, driven by early adoption of digital sustainability solutions, strong regulatory frameworks, and significant investments from both corporate and government sectors. Europe follows closely, propelled by ambitious climate targets and a mature digital infrastructure. The Asia Pacific region is emerging as a high-growth market, supported by rapid industrialization, urbanization, and increasing awareness of environmental issues among enterprises and governments. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as regional governments and corporations ramp up their sustainability efforts.

Component Analysis

The Carbon Footprint API Gateway market by component is segmented into Software, Hardware, and Services. The software segment dominates

Environmental monitoring stations (EMS) were installed in Campbelltown and Liverpool's CBD in December 2020. The EMS measures weather data and pollutants data. This dataset stores weather related measures (temperature, humidity, wind speed etc.)Associated Heat Stress Index is calculated based on a number of parameters. Data in this dataset is presented in the Quality of Place dashboard.Please note this data is indicative as sensors may from time to time provide incorrect data due to wear and tear or unforeseen circumstances.

This data provides results from field analyses, from the California Environmental Data Exchange Network (CEDEN). The data set contains two provisionally assigned values (“DataQuality” and “DataQualityIndicator”) to help users interpret the data quality metadata provided with the associated result. Due to file size limitations, the data has been split into individual resources by year. The entire dataset can also be downloaded in bulk using the zip files on this page (in csv format or parquet format), and developers can also use the API associated with each year's dataset to access the data. Users who want to manually download more specific subsets of the data can also use the CEDEN Query Tool, which provides access to the same data presented here, but allows for interactive data filtering.

Object-oriented Access to Environmental Documents (Ozone) in the context of the Digital Environment System Act. This service provides vector tiles that are shaped based on the object information in Ozone

FinTech Climate Data API Market Outlook

According to our latest research, the FinTech Climate Data API market size reached USD 1.23 billion globally in 2024, demonstrating robust momentum as financial institutions increasingly integrate climate data into their operations. The market is projected to grow at a CAGR of 22.7% from 2025 to 2033, reaching a forecasted value of USD 9.94 billion by 2033. This rapid expansion is driven by mounting regulatory pressures, rising investor demand for climate transparency, and the urgent need for financial entities to assess climate-related risks and opportunities.

A primary growth driver for the FinTech Climate Data API market is the global shift towards sustainable finance and the intensifying focus on environmental, social, and governance (ESG) criteria. Financial institutions are under increasing pressure from regulators and investors to quantify and disclose climate-related risks embedded in their portfolios. This has led to a surge in demand for sophisticated climate data APIs that can deliver real-time, granular, and actionable insights. These APIs enable banks, asset managers, and insurance companies to integrate climate risk analytics directly into their existing risk assessment, investment analysis, and compliance workflows. As a result, the market is witnessing accelerated adoption, particularly among organizations aiming to align with international frameworks such as the Task Force on Climate-related Financial Disclosures (TCFD) and the European Union’s Sustainable Finance Disclosure Regulation (SFDR).

Another significant factor propelling the FinTech Climate Data API market is the rapid digital transformation within the financial services sector. The proliferation of cloud computing, artificial intelligence, and big data analytics has enabled the development of advanced climate data solutions that are scalable, interoperable, and easily integrated via API infrastructure. Financial technology (FinTech) companies are leveraging these capabilities to offer innovative services such as climate-adjusted portfolio management, carbon accounting, and scenario analysis. This technological evolution is lowering barriers to entry for smaller financial institutions and fintech startups, broadening the market’s user base and fostering a competitive ecosystem. Moreover, the growing collaboration between climate data providers and financial software vendors is catalyzing the creation of end-to-end solutions tailored to specific use cases across banking, asset management, and insurance.

The increasing frequency and severity of climate-related events, such as floods, wildfires, and hurricanes, have heightened awareness of the financial risks associated with climate change. This has compelled financial institutions to seek more accurate and timely data to model potential impacts on asset values, loan portfolios, and insurance liabilities. The FinTech Climate Data API market is responding by offering APIs that aggregate and normalize data from diverse sources, including satellite imagery, meteorological data, and corporate emissions disclosures. By facilitating comprehensive risk modeling and scenario analysis, these APIs are becoming indispensable tools for financial decision-makers. The trend is particularly pronounced in developed markets, where regulatory frameworks and investor expectations are driving the integration of climate data into mainstream financial analysis.

From a regional perspective, North America and Europe currently dominate the FinTech Climate Data API market, accounting for the largest share of global revenues. This leadership is attributed to the presence of major financial hubs, stringent regulatory requirements, and a high level of technological maturity. However, the Asia Pacific region is emerging as a key growth engine, supported by rapid fintech adoption, expanding financial markets, and increasing government initiatives to promote sustainable finance. Latin America and the Middle East & Africa, while still nascent, are expected to offer significant opportunities as awareness of climate risk grows and digital infrastructure improves. The regional landscape is thus characterized by a dynamic interplay of regulatory, technological, and market-driven factors shaping the adoption of climate data APIs.