This statistic shows the projected top ten largest national economies in 2050. By 2050, China is forecasted to have a gross domestic product of over ** trillion U.S. dollars.

The impact of climate change has been forecasted to affect the economies of South-East Asian Nations (ASEAN) the hardest. The maximum projected loss incurred by the ASEAN in the event of a 3.2°C temperature rise is 37.4 percent. This is more than double the forecast loss of the Advanced Asia economies and 10 percent higher than the next largest forecast loss of the Middle East & Africa.

This statistic shows the top ten countries projected to have the greatest average annual growth in gross domestic product from 2016 to 2050. From 2016 to 2050, Vietnam is projected to have an average annual GDP growth rate of * percent.

Since the beginning of the 21st century, the BRICS countries have been considered the five foremost developing economies in the world. Originally, the term BRIC was used by economists when talking about the emerging economies of Brazil, Russia, India, and China, however these countries have held annual summits since 2009, and the group has expanded to include South Africa since 2010. China has the largest GDP of the BRICS country, at 16.86 trillion U.S. dollars in 2021, while the others are all below three trillion. Combined, the BRICS bloc has a GDP over 25.85 trillion U.S. dollars in 2022, which is slightly more than the United States. BRICS economic development China has consistently been the largest economy of this bloc, and its rapid growth has seen it become the second largest economy in the world, behind the U.S.. China's growth has also been much faster than the other BRICS countries; for example, when compared with the second largest BRICS economy, its GDP was less than double the size of Brazil's in 2000, but is almost six times larger than India's in 2021. Since 2000, the country with the second largest GDP has fluctuated between Brazil, Russia, and India, due to a variety of factors, although India has held this position since 2015 (when the other two experienced recession), and it's growth rate is on track to surpass China's in the coming decade. South Africa has consistently had the smallest economy of the BRICS bloc, and it has just the third largest economy in Africa; its inclusion in this group is due to the fact that it is the most advanced and stable major economy in Africa, and it holds strategic importance due to the financial potential of the continent in the coming decades. Future developments It is predicted that China's GDP will overtake that of the U.S. by the end of the 2020s, to become the largest economy in the world, while some also estimate that India will also overtake the U.S. around the middle of the century. Additionally, the BRICS group is more than just an economic or trading bloc, and its New Development Bank was established in 2014 to invest in sustainable infrastructure and renewable energy across the globe. While relations between its members were often strained or of less significance in the 20th century, their current initiatives have given them a much greater international influence. The traditional great powers represented in the Group of Seven (G7) have seen their international power wane in recent decades, while BRICS countries have seen theirs grow, especially on a regional level. Today, the original BRIC countries combine with the Group of Seven (G7), to make up 11 of the world's 12 largest economies, but it is predicted that they will move further up on this list in the coming decades.

From the IPCC website: The B2 world is one of increased concern for environmental and social sustainability. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R&D continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields.

1. Temporal Coverage of Data: The data collection periods are 2010, 2030, and 2050.2. Spatial Coverage and Projection:Spatial Coverage: GlobalLongitude: -180° - 180°Latitude: -90° - 90°Projection: GCS_WGS_19843. Disciplinary Scope: The data pertains to the fields of Earth Sciences and Geography.4. Data Volume: The total data volume is approximately 31.5 MB.5. Data Type: Raster (GeoTIFF)6. Thumbnail (illustrating dataset content or observation process/scene): · 7. Field (Feature) Name Explanation:a. Name Explanation: IND: Industrial Value Addedb. Unit of Measurement: Unit: US Dollars (USD)8. Data Source Description:a. Remote Sensing Data:2010 Global Vegetation Index data (Enhanced Vegetation Index, EVI, from MODIS monthly average data) and 2010 Nighttime Light Remote Sensing data (DMSP/OLS)b. Meteorological Data:From the CMCC-CM model in the Fifth International Coupled Model Intercomparison Project (CMIP5) published by the United Nations Intergovernmental Panel on Climate Change (IPCC)c. Statistical Data:From the World Development Indicators dataset of the World Bank and various national statistical agenciesd. Gross Domestic Product Data:Sourced from the project "Study on the Harmful Processes of Population and Economic Systems under Global Change" under the National Key R&D Program "Mechanisms and Assessment of Risks in Population and Economic Systems under Global Change," led by Researcher Sun Fubao at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciencese. Other Data:Rivers, roads, settlements, and DEM, sourced from the National Oceanic and Atmospheric Administration (NOAA), Global Risk Data Platform, and Natural Earth9. Data Processing Methods(1) Spatialization of Baseline Industrial Value Added: Using 2010 global EVI vegetation index data and nighttime light remote sensing data, we addressed the oversaturation issue in nighttime light data by constructing an adjusted nighttime light index to obtain the optimal global light data. The EANTIL model was developed using NTL, NTLn, and EVI data, with the following formula:Here, EANTLI represents the adjusted nighttime light index, NTL represents the original nighttime light intensity value, and NTLn represents the normalized nighttime light intensity value. Based on the optimal light index EANTLI and the industrial value-added data from the World Bank, we constructed a regression allocation model to derive industrial value added (I), generating the global 2010 industrial value-added data with the formula:Here, I represents the industrial value added for each grid cell, and Ii represents the industrial value added for each country, EANTLi derived from ArcGIS statistical analysis and the regression allocation model.(2) Spatial Boundaries for Future Industrial Value Added: Using the Logistic-CA-Markov simulation principle and global land use data from 2010 and 2015 (from the European Space Agency), we simulated national land use changes for 2030 and 2050 and extracted urban land data as the spatial boundaries for future industrial value added. To comprehensively characterize the influence of different factors on land use and considering the research scale, we selected elevation, slope, population, GDP, distance to rivers, and distance to roads as land use driving factors. Accuracy validation using global 2015 land use data showed an average accuracy of 91.89%.(3) Estimation of Future Industrial Value Added: Based on machine learning and using the random forest model, we constructed spatialization models for industrial value added under different climate change scenarios: Here, tem represents temperature, prep represents precipitation, GDP represents national economic output, L represents urban land, D represents slope, and P represents population. The random forest model was constructed using factors such as 2010 industrial value added, urban land distribution, elevation, slope, distances to rivers, roads, railways (considering transportation), and settlements (considering noise and environmental pollution from industrial buildings), along with temperature and precipitation as climate scenario data. Except for varying temperature and precipitation values across scenarios, other variables remained constant. The model comprised 100 decision trees, with each iteration randomly selecting 90% of the samples for model construction and using the remaining 10% as test data, achieving a training sample accuracy of 0.94 and a test sample accuracy of 0.81.By analyzing the proportion of industrial value added to GDP (average from 2000 to 2020, data from the World Bank) and projected GDP under future Shared Socioeconomic Pathways (SSPs), we derived future industrial value added for each country under different SSP scenarios. Using these projections, we constructed regression models to allocate future industrial value added proportionally, resulting in spatial distribution data for 2030 and 2050 under different SSP scenarios.10. Applications and Achievements of the Dataseta. Primary Application Areas: This dataset is mainly applied in environmental protection, ecological construction, pollution prevention and control, and the prevention and forecasting of natural disasters.b. Achievements in Application (Awards, Published Reports and Articles):Achievements: Developed a method for downscaling national-scale industrial value-added data by integrating DMSP/OLS nighttime light data, vegetation distribution, and other data. Published the global industrial value-added dataset.

It is estimated that more than 8 billion people live on Earth and the population is likely to hit more than 9 billion by 2050. Approximately 55 percent of Earth’s human population currently live in areas classified as urban. That number is expected to grow by 2050 to 68 percent, according to the United Nations (UN).The largest cities in the world include Tōkyō, Japan; New Delhi, India; Shanghai, China; México City, Mexico; and São Paulo, Brazil. Each of these cities classifies as a megacity, a city with more than 10 million people. The UN estimates the world will have 43 megacities by 2030.Most cities' populations are growing as people move in for greater economic, educational, and healthcare opportunities. But not all cities are expanding. Those cities whose populations are declining may be experiencing declining fertility rates (the number of births is lower than the number of deaths), shrinking economies, emigration, or have experienced a natural disaster that resulted in fatalities or forced people to leave the region.This Global Cities map layer contains data published in 2018 by the Population Division of the United Nations Department of Economic and Social Affairs (UN DESA). It shows urban agglomerations. The UN DESA defines an urban agglomeration as a continuous area where population is classified at urban levels (by the country in which the city resides) regardless of what local government systems manage the area. Since not all places record data the same way, some populations may be calculated using the city population as defined by its boundary and the metropolitan area. If a reliable estimate for the urban agglomeration was unable to be determined, the population of the city or metropolitan area is used.Data Citation: United Nations Department of Economic and Social Affairs. World Urbanization Prospects: The 2018 Revision. Statistical Papers - United Nations (ser. A), Population and Vital Statistics Report, 2019, https://doi.org/10.18356/b9e995fe-en.

We provide free TelluBase data to select public data sources.These are small, but important, subsets of the full product.To start with, we offer all Latin American countries (except Venezuela) with GDP per city and subdivision in 2023 in these PDFs.If you represent an academic institution or a reputable media outlet and think you may benefit from TelluBase data, we may be able to provide it for free. Contact me with your query at scanback@tellusant.comTelluBase covers 218 countries, 2600 cities, and 2500 subdivisions, 2000-2050. It gives a completely exhaustive view of the world economy.

Armenia’s economy is fueled by imported natural gas. The country’s power, heating, and transport sectors rely heavily on natural gas, and the energy intensity of Armenia’s gross domestic product (GDP) is higher than the global average. Natural gas represents up to 63 percent of Armenia’s total energy supply, one of the world’s largest shares, and all of it is imported, mostly from the Russian Federation, creating a high vulnerability to external shocks. The high share of natural gas puts Armenia below the global average in terms of greenhouse gas (GHG) emissions, at 3.8 tonnes of carbon dioxide equivalent (tCO2e) per capita in 2019, driven by the energy sector (two third of emissions) followed by theagriculture sector. Decarbonization provides energy security at zero or even negative costs, when considering the full economic costs of fossil fuels, and acts as an insurance against the uncertainty around future gas prices. Energy security risks provide a clear incentive for Armenia to develop domestic renewable resources. As gas has historically been imported at relatively low costs (the current price of $180 per 1,000 standard cubic meters is substantially below international gas price benchmarks), an increase in natural gas prices to meet international benchmarks would immediately make the low-carbon transition a no-regret decision. A scenario in which Armenia diversifies its gas imports and pays international gas prices would lead to a higher energy system cost than a decarbonization scenario in which Armenia transitions from a gas-powered to a solar-powered economy and reduces emissions to its target of 2.07 tCO2e per capita by 2050.

As per Cognitive Market Research's latest published report, the Global Non-Stick Cookware market size will be $13,628.21 Million by 2028.The Global Non-Stick Cookware Industry's Compound Annual Growth Rate will 3.73% from 2023 to 2030.

The North America Non-Stick Cookware market size will be USD 4,572.27 Million by 2028.

Factors Affecting the Non Stick Cookware Market

Increasing population ratio and rapid urbanization in emerging countries

China and India are the world's biggest creating economies and furthermore two of the most crowded nations. China, which presently has more than 1.3 billion individuals, is required to develop to more than 1.4 billion by 2050, and India with a population of 1 billion will surpass China to be the most crowded nation with about a 1.6 billion population. These population giants are home to 37% of the total population today. Also, China and India have made eminent progress in their financial improvement described by a high pace of GDP development over the most recent two decades. Together the two nations account as of now for just about a fifth of world GDP.

Developing nations, for example, India and China have abounding population besting the one-billion imprints; both experienced the progress from a shut economy to a more market–situated commitment with the outside world in exchange and speculation; and both to date are in the procedures of industrialization and modernization joined by significant rates of economic growth.

The rapid urbanization in many countries including developed nations over the past 50 years appears to have been joined by unnecessarily elevated levels of grouping of the urban population in extremely enormous urban communities. In any case, in a develop arrangement of urban communities, economic activity is increasingly spread out. Since forever, urban areas have been the primary habitats of learning, culture and development.

It is not surprising that the world's most urban countries tend to be the richest and have the highest human development. Progressing rapid urbanization can possibly improve the prosperity of social orders. Albeit just around a large portion of the world's kin live in urban areas, they create in excess of 80 percent of Global Domestic Product (GDP).

Due to growing population and urbanization people spending capacity has also increased gradually. People give preference to the health development. Additionally, increasing urbanization results in surging nuclear family which enhances the demand for kitchen appliances and cookware. Moreover, rise in working-class population prefers quickly made home-cooked healthy food with the help of modern kitchen appliances that results in mounting of demand for non-stick cookware.

Following graph shows the, world's population who lives in urban area. Also, every region provides the growth ratio of their population from year 1990 till forecast year 2050. All in one this analysis shows how population growth impacts on rapid urbanization. According to graph, Asia Pacific region’s population growth is expected to grow in forecast period.

Varieties of non-stick cookware and wide availability in retail channels

Restraints for Non-Stick Cookware Market

Availability of substitute products. (Access Detailed Analysis in the Full Report Version)

Opportunities for Non-Stick Cookware Market

Rise in disposable income and spending habits. (Access Detailed Analysis in the Full Report Version)

Introduction of Non Stick Cookware

A non-stick cookware is a kitchen cookware such as non-stick pans that has a non-stick surface engineered to reduce the ability of other materials to stick to it. It ensures quick proper cooking of the food in the cookware without sticking. The commonly used non-stick coating cookware is Teflon, ceramic coated cookware.

There are various benefits of non-stick cookware such as affordable, lightweight, easy to handle provides easy cleaning of food. The non-stick cookware in form of frying pans, saucepan, griller, casseroles are made up of different coating material such as Teflon, ceramic coated, anodized aluminum, these are durable, user-friendly, scratch resistant and are stable at temperature till 300 degree Celsius. They use less oil and allows even heat distribution that enhances the flavors of dish and quick heating enables quicker cooking of t...

Global patterns of current and future road infrastructure - Supplementary spatial data

Authors: Johan Meijer, Mark Huijbregts, Kees Schotten, Aafke Schipper

Research paper summary: Georeferenced information on road infrastructure is essential for spatial planning, socio-economic assessments and environmental impact analyses. Yet current global road maps are typically outdated or characterized by spatial bias in coverage. In the Global Roads Inventory Project we gathered, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into a global roads dataset. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets. We then related total road length per country to country area, population density, GDP and OECD membership, resulting in a regression model with adjusted R2 of 0.90, and found that that the highest road densities are associated with densely populated and wealthier countries. Applying our regression model to future population densities and GDP estimates from the Shared Socioeconomic Pathway (SSP) scenarios, we obtained a tentative estimate of 3.0–4.7 million km additional road length for the year 2050. Large increases in road length were projected for developing nations in some of the world's last remaining wilderness areas, such as the Amazon, the Congo basin and New Guinea. This highlights the need for accurate spatial road datasets to underpin strategic spatial planning in order to reduce the impacts of roads in remaining pristine ecosystems.

Contents: The GRIP dataset consists of global and regional vector datasets in ESRI filegeodatabase and shapefile format, and global raster datasets of road density at a 5 arcminutes resolution (~8x8km). The GRIP dataset is mainly aimed at providing a roads dataset that is easily usable for scientific global environmental and biodiversity modelling projects. The dataset is not suitable for navigation. GRIP4 is based on many different sources (including OpenStreetMap) and to the best of our ability we have verified their public availability, as a criteria in our research. The UNSDI-Transportation datamodel was applied for harmonization of the individual source datasets. GRIP4 is provided under a Creative Commons License (CC-0) and is free to use. The GRIP database and future global road infrastructure scenario projections following the Shared Socioeconomic Pathways (SSPs) are described in the paper by Meijer et al (2018). Due to shapefile file size limitations the global file is only available in ESRI filegeodatabase format.

Regional coding of the other vector datasets in shapefile and ESRI fgdb format:

• Region 1: North America
• Region 2: Central and South America
• Region 3: Africa
• Region 4: Europe
• Region 5: Middle East and Central Asia
• Region 6: South and East Asia
• Region 7: Oceania

Road density raster data:

• Total density, all types combined
• Type 1 density (highways)
• Type 2 density (primary roads)
• Type 3 density (secondary roads)
• Type 4 density (tertiary roads)
• Type 5 density (local roads)

Keyword: global, data, roads, infrastructure, network, global roads inventory project (GRIP), SSP scenarios

Tellusant provides free TelluBase data to select public data sources.These are small, but important, subsets of the full product.We are currently expanding the availability of Middle East & North Africa. To begin with, provide Saudi Arabia and United Arab Emirates city and subdivision data for 2023.We plan to add Egypt, Morocco, Algeria, and Tunisia before the end of July 2025. We will also update all data to reflect 2024 values.If you represent an academic institution or a reputable media outlet and think you may benefit from TelluBase data, we may be able to provide it for free. Contact us with your query at info@tellusant.com.TelluBase covers 218 countries, 2600 cities, and 2500 subdivisions, 2000-2050. It gives a completely exhaustive view of the world economy.

Armenia’s economy is fueled by imported natural gas. The country’s power, heating, and transport sectors rely heavily on natural gas, and the energy intensity of Armenia’s gross domestic product (GDP) is higher than the global average. Natural gas represents up to 63 percent of Armenia’s total energy supply, one of the world’s largest shares, and all of it is imported, mostly from the Russian Federation, creating a high vulnerability to external shocks. The high share of natural gas puts Armenia below the global average in terms of greenhouse gas (GHG) emissions, at 3.8 tonnes of carbon dioxide equivalent (tCO2e) per capita in 2019, driven by the energy sector (two third of emissions) followed by the agriculture sector. Decarbonization provides energy security at zero or even negative costs, when considering the full economic costs of fossil fuels, and acts as an insurance against the uncertainty around future gas prices. Energy security risks provide a clear incentive for Armenia to develop domestic renewable resources. As gas has historically been imported at relatively low costs (the current price of $180 per 1,000 standard cubic meters is substantially below international gas price benchmarks), an increase in natural gas prices to meet international benchmarks would immediately make the low-carbon transition a no-regret decision. A scenario in which Armenia diversifies its gas imports and pays international gas prices would lead to a higher energy system cost than a decarbonization scenario in which Armenia transitions from a gas-powered to a solar-powered economy and reduces emissions to its target of 2.07 tCO2e per capita by 2050.

Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform their choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for the exploration of such scenarios. At IMPACT's core is a partial equilibrium, the multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research center through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP). This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and trade of major food commodity groups, by regions and country. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).

Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform their choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for exploration such scenarios. At IMPACT's core is a partial equilibrium, multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research centers through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP). This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and trade of major food commodity groups, by regions and country. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).

From 2020 to 2050, the largest per capita economic loss due to chronic obstructive pulmonary disease (COPD) is expected to occur in the World Bank region of North America, estimated at around ***** 2017 international dollars per capita. This is followed by the region of Europe and Central Asia, with *** 2017 international dollars worth of economic loss per capita.

The statistic shows gross domestic product (GDP) per capita in Indonesia from 1987 to 2023, with projections up until 2030. GDP is the total value of all goods and services produced in a country in a year. It is considered to be a very important indicator of the economic strength of a country and a positive change is an indicator of economic growth. In 2023, the GDP 29per capita in Indonesia amounted to around 4,919.94 U.S. dollars. Indonesia's gross domestic product on the rise Indonesia has the largest economy in Southeast Asia is considered one of the most important emerging market economies in the world. Indonesia is a member of the G-20 economies and a founding member of ASEAN. It has one of the largest gross domestic products in the world: In 2014, the Indonesian GDP was reported to exceed 856 billion U.S. dollars. GDP in Indonesia has been increasing rapidly and in 2011, it was estimated that it had grown by more than 6.4 percent in comparison to the previous year. That same year, global GDP amounted to more than 72 trillion U.S. dollars - with the exception of 2009, global GDP has been continuously increasing each year over the past decade. Based on purchasing power parity, Indonesia's share in the global GDP is significantly higher than that of other major economies, and in 2014 was almost on the same level with France and higher than the UK's share. According to a forecast by Goldman Sachs, Indonesia will be among the 15 countries with the largest gross domestic product worldwide by 2030. In addition, the gross domestic product per capita in Indonesia has also undergone a rapid increase. Over the past decade, GDP per capita in Indonesia has quadrupled, a remarkable feat seldom seen in any economy.

The Gross Domestic Product (GDP) in Montenegro was worth 8.07 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Montenegro represents 0.01 percent of the world economy. This dataset provides the latest reported value for - Montenegro GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

From the IPCC website: The B2 world is one of increased concern for environmental and social sustainability. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R&D continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields.

In 2023, the estimated total GDP of all ASEAN states amounted to approximately 3.8 trillion U.S. dollars, a significant increase from the previous years. In fact, the GDP of the ASEAN region has been skyrocketing for a few years now, reflecting the region’s thriving economy. Power in the EastThe Association of Southeast Asian Nations (ASEAN) comprises Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. It was established in 1967 among five of these countries (Indonesia, Malaysia, Thailand, Singapore, and the Philippines) to facilitate trade and economic growth, as well as promote cultural development and social structures in the region. To date, they have been joined by another five nations. The ASEAN marketThe founding of the ASEAN organization provides the collaborating nations with more autonomy and influence on the global economy than they would have had by themselves. Additionally, struggling participating countries, such as Laos, are given an opportunity to grow on an ASEAN single market.