Statista estimates have created a hypothetical forecast of the potential cost to residential real estate due to rising sea-levels if no further action is taken to mitigate risks across Europe. The estimate, which takes 2020 estimates into account for total populations, populations below locked-in seas levels, the number of residential buildings in at-risk areas and the average size and cost of real estate by city. The scenario measures lower and upper estimates for global average temperature changes by 2100. Far more can be learnt on the potential costs to real estate in Europe through sea-level rises in our report. As well as giving easy to digest figures, the report also covers a global perspective and how each city is combating the growing threat of coastal and river flooding due to climate change.

This dataset tracks annual reduced-price lunch eligibility from 2002 to 2023 for Rise vs. California and Lancaster Elementary School District

This dataset contains the predicted prices of the asset Rise of PNUT over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains calculated rates of sea-level rise derived from the nearest NOAA National Water Level Observation Network (NWLON) stations relevant for each tidal wetland monitoring site. Calculated rates include the entire record for long-term, as well as more limited dataset for more recent 19-year rates. The 19-year rates were calculated to end at the most recent surface elevation table (SET) measurement. Rates are directly compared with rates from SET measurements of surface elevation change to provide estimates of vulnerability to sea level rise.

When surveyed in March 2023, some ** percent of respondents in Belgium stated that they expected grocery prices to increase. This figure has increased since the start of the survey period in September 2021 and peaked in December 2022.

Sea-level rise (SLR) through the twenty-first century and beyond is inevitable, threatening coastal areas and their inhabitants unless there is appropriate adaptation. We investigate coastal flooding to 2100 under the full range of IPCC AR6 (2021) SLR scenarios, assuming plausible adaptation. The adaptation selects the most economically robust adaptation option: protection or retreat. People living in unprotected coastal areas that are frequently inundated (below 1-in-1-year flood level) are assumed to migrate, and the land is considered lost. Globally, across the range of SLR and related socioeconomic scenarios, we estimate between 4 million and 72 million people could migrate over the twenty-first century, with a net land loss ranging from 2,800 to 490,000 km2. India and Vietnam consistently show the highest absolute migration, while Small Island Developing States are the most affected when considering relative migration and land loss. Protection is the most robust adaptation option under all scenarios for 2.8% of the global coastline, but this safeguards 78% of the global population and 91% of assets in coastal areas. Climate stabilisation (SSP1–1.9 and SSP1–2.6) does not avoid all coastal impacts and costs as sea levels still rise albeit more slowly. The impacts and costs are also sensitive to the socioeconomic scenario: SSP3–7.0 experiences higher migration than SSP5–8.5 despite lower SLR, reflecting a larger population and lower GDP. Our findings can inform national and intergovernmental agencies and organisations on the magnitude of SLR impacts and costs and guide assessments of adaptation policies and strategies.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average (CUSR0000SASLE) from Jan 1967 to Sep 2025 about energy, urban, consumer, CPI, services, inflation, price index, indexes, price, and USA.

Food price increases hit the egg category the hardest between December 2021 and December 2024 in the United States. The price of eggs increased by **** percent in 2024.

This dataset contains the predicted prices of the asset Infinity Rising over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Natural gas rose to 4.94 USD/MMBtu on December 3, 2025, up 2.04% from the previous day. Over the past month, Natural gas's price has risen 13.71%, and is up 62.29% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Natural gas - values, historical data, forecasts and news - updated on December of 2025.

According to a survey taken in July 2025, roughly 27percent of surveyed Americans were planning to make purchases because they expected prices to increase as a result of the tariffs.

This survey explores what respondents see as the main contributors to rising real energy prices over the next 40 years. ** percent of respondents saw dwindling supplies of non-renewable energy commodities as a main contributor. Respondents could select up to *****.

This raster GIS dataset contains 5-meter-resolution cells depicting the areas of LOW marsh gain (value=1), lost (value=-1) and remaining (no change; value=0). Low marsh (LM) was defined as regularly flooded marsh [SLAMM category 8]. LM is normally inundated by tidal water at least once per day. Based on SLAMM simulation outputs, we generated the gain and loss map by using the “Raster Calculator” tool under “Spatial Analyst Tools” in ArcGIS software. The methodology consists of the three steps listed below (where we use low marsh [LM] as an example). The same process can be applied to other SLAMM land cover categories. 1) Open ArcMap, add SLAMM simulation raster outputs (all SLAMM categories) for baseline year and future years. 2) In Raster Calculator, set the SLAMM codeequal to8 (low marsh = SLAMM category 8) to generate a new raster. Each individual cell in the new raster is assigned a value of “0” or “1”. “1” is low marsh and “0” is any other SLAMM land cover category. Perform this step for both the baseline year and future year. 3) In Raster Calculator, subtract the new raster for the baseline year from the new raster for the future year (formula = new future year raster - new baseline year raster). The calculation generates a new raster, in which each individual cell is assigned a value of “-1”, “0”, or “1”. Based on the calculation, “-1” means low marsh loss in the future (the cell has converted from low marsh to a different SLAMM category), “0” means low marsh is remaining (the cell stays the same), and “1” means low marsh gain in the future (the cell has converted from a different SLAMM category to low marsh). Prior SLAMM work has been performed in the Delaware Bay, but our methods differ in that we derive results for specific marsh areas and utilize more recent, higher resolution elevation data (2015 USGS CoNED Topobathy Model: New Jersey and Delaware), the most recent SLR projections, and site-specific accretion data (through 2016). These SLAMM simulations were performed as part of a larger project by the USEPA on frameworks and methods for characterizing relative wetland vulnerabilities. Note: additional raster files from this project are available upon request. These include files from low and high SLR scenarios and different model protection scenarios. For more information, contact Jordan West (West.Jordan@epa.gov).

Learn about the multiple factors influencing cement prices, the global shift towards eco-friendly products, and the rising demand in India and UAE. Cement prices continue to rise due to increasing demand for sustainable cement and rising transportation and raw material costs.

Vulnerability was assessed for the main Hawaiian Islands using the outputs of coastal hazard exposure modeling (provided separately). Potential economic loss was based on the value of the land and structures from the county tax parcel database permanently lost in the sea level rise exposure area (SLR-XA) for four future sea level rise scenarios: 0.5 foot, 1.1 foot, 2.0 feet and 3.2 feet based on the upper end of the IPCC AR5 RCP8.5 projections. This particular layer depicts potential economic loss using the 1.1-ft (0.3224-m) sea level rise scenario. While the RCP8.5 predicts that this scenario would be reached by the year 2050, questions remain around the exact timing of sea level rise and recent observations and projections suggest a sooner arrival. Potential economic loss was analyzed individually for each hazard (passive flooding, annual high wave flooding, or coastal erosion) at the parcel level and subsequently aggregated in 1-hectare (100 square meter or 1,076 square foot) grids. For the islands of Hawaii, Lanai, and Molokai, the potential economic loss was based solely on passive flooding. Potential economic loss in the SLR-XA area was determined from the highest loss value of any one hazard within the 1-hectare grid, thus avoiding double counting a loss of a particular asset from multiple hazards. Those maximum values for each sector are then summed to determine the total economic loss to property in each grid. Assumptions and Limitations: The vulnerability assessment addressed exposure to chronic flooding with sea level rise. Key assumptions of the economic analysis for the SLR-XA included: (a) loss is permanent; (b) economic loss is based on the value in U.S. dollars in 2016 as property values in the future are unknown; (c) economic loss is based on the value of the land and structures exposed to flooding in the SLR-XA excluding the contents of the property and does not include the economic loss or cost to replace roads, water conveyance systems and other critical infrastructure; and (d) no adaptation measures are put in place that could reduce impacts in the SLR-XA. Economic value data were not available for length of roads, water and wastewater lines, and other public infrastructure due to the variable cost of such infrastructure depending on location, and the complexity and uncertainty involved in design, siting, and construction. Additionally, environmental assets such as beaches and wetlands were not assessed economically due to the complexity in valuing ecosystem services. The loss of both public infrastructure and environmental assets from flooding would result in significant economic loss. Therefore, the total potential economic loss figures estimated in these data are likely an underestimate. Data compiled by the Pacific Islands Ocean Observing System (PacIOOS) for the Hawaii Sea Level Rise Viewer hosted at https://pacioos.org/shoreline/slr-hawaii/. For further information, please see the Hawaii Sea Level Rise Vulnerability and Adaptation Report: https://climateadaptation.hawaii.gov/wp-content/uploads/2017/12/SLR-Report_Dec2017.pdf.

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.

Japan RM&C: Retail: Curr. Term (YoY): Rise data was reported at 72.400 % in Mar 2025. This records an increase from the previous number of 70.400 % for Dec 2024. Japan RM&C: Retail: Curr. Term (YoY): Rise data is updated quarterly, averaging 30.200 % from Jun 2005 (Median) to Mar 2025, with 80 observations. The data reached an all-time high of 72.400 % in Mar 2025 and a record low of 11.400 % in Mar 2010. Japan RM&C: Retail: Curr. Term (YoY): Rise data remains active status in CEIC and is reported by The Small and Medium Enterprise Agency. The data is categorized under Global Database’s Japan – Table JP.S086: SME Business Survey Report: Price.

Pilot Programs for Advanced Heat Pumps Market Outlook

According to our latest research, the global market size for Pilot Programs for Advanced Heat Pumps reached USD 2.85 billion in 2024, with a robust CAGR of 13.2% projected from 2025 to 2033. By the end of 2033, the market is anticipated to achieve a value of USD 8.52 billion. This remarkable growth trajectory is primarily driven by increasing global investments in energy efficiency, decarbonization initiatives, and the urgent need to transition from fossil fuel-based heating systems to more sustainable alternatives. As per our latest research, government incentives and regulatory mandates are acting as significant catalysts, propelling the adoption and expansion of advanced heat pump pilot programs worldwide.

One of the primary growth factors for the Pilot Programs for Advanced Heat Pumps Market is the intensifying global focus on reducing greenhouse gas emissions and meeting climate targets under international agreements such as the Paris Accord. Governments across North America, Europe, and Asia Pacific are rolling out comprehensive policy frameworks and funding mechanisms to accelerate the deployment of advanced heat pump technologies. These pilot programs serve as critical platforms for validating the technical, economic, and environmental feasibility of next-generation heat pumps in real-world settings. Additionally, advancements in heat pump technology, such as improved efficiency, lower operational costs, and enhanced integration with renewable energy sources, are making these solutions increasingly attractive for both residential and commercial users. The synergy between regulatory incentives and technological innovation is expected to sustain strong market momentum over the next decade.

Another key driver is the rising demand for energy-efficient heating, cooling, and water heating solutions in both mature and emerging economies. As urbanization accelerates and energy costs rise, households, businesses, and public sector entities are actively seeking alternatives that offer superior performance and lower life-cycle costs. Pilot programs serve as testbeds for new business models, financing structures, and user engagement strategies, enabling stakeholders to address technical and market barriers before full-scale deployment. The growing emphasis on electrification of heating, supported by smart grid integration and digital monitoring, further enhances the value proposition of advanced heat pumps. These pilots are also instrumental in building consumer awareness and trust, which are essential for achieving widespread adoption.

Moreover, the increasing involvement of utilities, private investors, and public sector organizations in funding and implementing pilot programs is expanding the market's reach and impact. Utility-led pilots are leveraging advanced data analytics and demand response technologies to optimize system performance and grid stability, while private sector initiatives are focusing on innovative financing and service delivery models. The collaboration between technology providers, installers, and research institutions is fostering a vibrant ecosystem that supports continuous product improvement and knowledge sharing. As a result, the market for pilot programs for advanced heat pumps is evolving rapidly, with new entrants and established players alike seeking to capitalize on emerging opportunities across diverse application domains.

Regionally, Europe remains at the forefront of the market, accounting for the largest share of pilot program deployments in 2024. The region's leadership is underpinned by ambitious climate policies, substantial funding allocations, and a mature energy infrastructure that facilitates the integration of advanced heat pump technologies. North America is also experiencing significant growth, driven by state-level mandates and utility incentives, while Asia Pacific is emerging as a high-potential market due to rapid urbanization and government-led clean energy initiatives. Latin America and the Middle East & Africa, though currently smaller in scale, are expected to witness accelerated adoption as pilot program outcomes demonstrate the viability and benefits of advanced heat pumps in diverse climatic and socioeconomic contexts.

Program Type Analysis

The Program Type segment of the Pilot Programs for Advanced Heat Pumps Market is broadly categorized into Residential, Commercial, and Industrial programs. Residential pilot programs are witnessing substantial trac