CO2 emissions fell by roughly one percent in 2024 in China. In the first quarter of 2025, CO2 emission even fell by 1.6 percent. According to estimates, China can reach peak emissions in 2025, despite increasing energy demand. This is possible due to investments in the construction of renewable energy infrastructure.

In 2023, excavators emitted around 38 percent of nitrogen oxides among all engineering machinery vehicles in China. Vehicles were one of the main sources of air pollution in China.

Africa accounted for approximately 3.7 percent of the world's emissions of carbon dioxide (CO2) from fossil fuels and industry in 2023. Over the last two decades, the continent's contribution to the global carbon emissions fluctuated between 3.4 percent and 3.9 percent - the smallest share among all world's regions.

Social media is a transformative digital technology, collapsing the "six degrees of separation" which have previously characterised many social networks, and breaking down many of the barriers to individuals communicating with each other. Some commentators suggest that this is having profound effects across society, that social media has revolutionised the communication of controversial public issues such as climate change, and that this has significantly increased the volume and variety of scientists, politicians, journalists, non-governmental organisations, think tanks and members of the public in contact with each other. Tweets were collected in response to the airing of the BBC programme "Climate Change: The Facts", broadcast on April 18th, 2019. https://www.imdb.com/title/tt10095266/ https://www.bbc.co.uk/iplayer/episode/m00049b1/climate-change-the-facts The data deposited is a list of 87,177 tweet IDs, which can be used to retrieve tweets.

Introduction

Climate-Smart Agriculture Statistics: Climate-Smart Agriculture (CSA) is certainly a new practice in agriculture, addressing the current challenges of climate change and population increase demand in food supply. These are the three main objectives: sustainably increasing productivity in agriculture, adapting and building resilience to climate change, and reducing or removing greenhouse gas emissions.

It's 2024, and many countries and organisations are scaling up CSA principles as a global framework. This article presents the latest Climate-Smart agriculture statistics, trends, and economic impacts for 2024.

The latest National Statistics on forestry produced by the Forestry Commission were released on 28 September 2017 according to the arrangements approved by the UK Statistics Authority.

Detailed statistics are published in the web publication Forestry Statistics 2017, with an extract in Forestry Facts & Figures 2017. They include UK statistics on woodland area, planting, timber, trade, climate change, environment, recreation, employment and finance & prices as well as some statistics on international forestry. Where possible, figures are also provided for England, Wales, Scotland and Northern Ireland.

This dataset covers statistics on carbon in forests, the Woodland Carbon Code and public attitudes to climate change. Attribution statement:

Communicating the "97%"’ scientific consensus has been the centerpiece of the effort to persuade climate skeptics. Still, this strategy may not work well for those who mistrust climate scientists, to begin with. We examine how the American public---Republicans in particular---respond when provided with a relatively detailed causal explanation summarizing why scientists have concluded that human activities are responsible for climate change. Based on a preregistered survey experiment (N = 3007) we assessed the effectiveness of detailed causal evidence vs. traditional consensus messaging. We found that both treatments had noticeable effects on belief in human-caused climate change, with the causal evidence being slightly more effective, though we did not observe equivalent patterns in changes in attitudes toward climate policies. We conclude that conveying scientific information serves more as a remedy than a cure, reducing but not eliminating misperceptions about climate change and opposition to climate policies.

Introduction

Air pollution Statistics: The air pollution problem is by far the most significant environmental health issue around the world and causes an estimated 7.7 million deaths each year. Climate change and air pollution are closely linked since every major pollutant has an impact on climate and many have common causes with greenhouse gases. Enhancing the quality of air can lead to improved health, development, and environmental benefits.

According to UNEP Pollution Action Note, the global condition of pollution in the air, its major sources, the effects of the air pollution on health as well as the national efforts to address this problem. The tiny particles that pollute the air are mostly derived from human activities such as burning fossil fuels for transportation, waste-burning electricity agriculture, and the major source of ammonia and methane as well as the mining and chemical industries. Let's look into air pollution and its impact.

The objective of this work includes the coastal scenario, risks and development of coastal paleoclimatology through landscape mapping; by highlighting the devastating climate change impacts that might result in tsunami in South-East Asian sea basin with short or no-awareness period; despite the facts that the Southeast Asia region is generally poor being encompassed by twelve countries along with the Indian and Pacific Oceans. Special payable concern to the Bay of Bengal has been paid that can dictate region’s climate to certain extent. The ecosystems’ impact due to climate change and global warming -can bring direct variables and affects in –salinity, temperature, river flow, runoff, soil characteristics, erosion, nutrition level and water quality. The landscape mapping can address the system infrastructure requirements to the SEAR’s sea basin attainable by the annual monsoons, the Southwest and the Northeast Monsoons. How recent meteorological and geodynamic-genetic events can result in adverse economical damages and significant losses of lives are also drawn. This work monitors on Sea-level rise gets projected under global warming. The most brainstorming findings from climate change issues are how the high latitudes for SEAR Sea Basins’ are likely to experience greater warming than the global mean and warming,- And how the hydrological cycle gets found responsible for bringing more floods and more droughts in- causing huge devastating changes for environmental factors in coastal zones

Emergent scientific facts about climate change occurrence, increasing intensity and potential damage to the world have made the issue of policy a necessity objective. In spite of global effort, very little data have been collected and therefore very little is known about support or opposition to mitigation or adaptation policies at any level. Although there are claims that support or opposition to proposed climate policies will be greatly influenced by perceived risks, how this evolves for farmers in a developing country is not understood and may be intricately intertwined with individuals' interpretation of practical experience with climate change impacts. Using a checklist, specific issues relating to climate change are covered through focus group discussions. Results of data analysis show widespread awareness of climate change impacts, reasonable ability to describe its occurrence but lack of fair understanding of the causes of climate change. Impact occurrences from experience and historical accounts are identified determinants in farmers' awareness, concern and risk perception of climate change and thus factor in the identification of relevant policies and decision to support them. The responsibility for ensuring policy effectiveness is said to involve the participatory roles of the farmers themselves, government, non-governmental organizations and international agencies.

African countries showed low resilience to climate change, according to the source's index. All assessed nations in Africa scored below 40 out of 100 points, classifying them as lower resilient countries. The Climate Resilience Index evaluated 180 nations worldwide, taking into account GDP as well as readiness and vulnerability to climate change. In Africa, Mauritius ranked as the most resilient country to climate change (56th worldwide). On the other hand, Chad was the least resilient, both in the African continent and globally.

Climate change poses an unprecedented level of threat to life on the planet. In addition, predictions about the scale and speed of impact are continually being revised upwards, so that what was already a serious situation continues to look even more threatening. The facts are well known. Atmospheric greenhouse gases are creating warmer temperatures, ice melt, sea-level rise and an unpredictable climate, with a range of extremely serious and hard-to-predict consequences. Recent research shows an increasingly bleak picture. During the period of writing this report new information suggests that: we may already be too late to prevent widespread collapse of coral reef systems due to ocean acidification; climate change adaptation will cost US$75-100 billion a year from 2010 onwards for developing countries according to the World Bank; and climate change may move faster than expected with average temperatures rising 4ºC by 2060 compared to pre-industrial levels according to the UK Meteorological Office. But serious as the situation has now become, much can still be done to reduce the problems created by climate change. This report focuses on the role that protected areas can play in mitigating and adapting to climate change; a set of options that hitherto has been under-represented in global response strategies. In the rush for “new” solutions to climate change, we are in danger of neglecting a proven alternative.Available onlineCall Number: [EL],551.6 STEISBN/ISSN: 978-2-88085-308-2Physical Description: 130 p.

Description

This data set contains the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. It contains the full set of samples for the global projections (under ar6.zip), as well as summary relative sea level projections (under ar6-regional-confidence.zip and, without the AR6 estimate of background sea level process rates, ar6-regional_novlm-confidence.zip). Most users will want to focus on the confidence_output_files, which correspond most directly to the figures and tables in the report. For the global projections, samples from the individual probability distributions described in AR6 WG1 9.6.3 are in the full_sample* directories.

Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool.

See https://zenodo.org/communities/ipcc-ar6-sea-level-projections for additional related data sets.

Required Acknowledgements and Citation

In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used:

• Fox-Kemper, B., H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, R. E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, A. B. A. Slangen, Y. Yu, 2021, Ocean, Cryosphere and Sea Level Change. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu and B. Zhou (eds.)]. Cambridge University Press. In press.
  
• Garner, G. G., R. E. Kopp, T. Hermans, A. B. A. Slangen, G. Koubbe, M. Turilli, S. Jha, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, in prep. Framework for Assessing Changes To Sea-level (FACTS). Geoscientific Model Development.
  
• Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5281/zenodo.5914709.

Please also include in the acknowledgements of works citing these projections:

We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea Level Change Team for developing and hosting the IPCC AR6 Sea Level Projection Tool.

IPCC AR6 Licensing

The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.

The latest National Statistics on forestry produced by the Forestry Commission were released on 26 September 2019 according to the arrangements approved by the UK Statistics Authority.

Detailed statistics are published in the web publication Forestry Statistics 2019, with an extract in Forestry Facts & Figures 2019. They include UK statistics on woodland area, planting, timber, trade, carbon, environment, social, employment and finance & prices as well as some statistics on international forestry. Where possible, figures are also provided for England, Wales, Scotland and Northern Ireland.

This dataset covers statistics on carbon in forests, the Woodland Carbon Code and public attitudes to climate change. In previous editions of Forestry Statistics this chapter was titled 'UK Forests and Climate Change'. Attribution statement:

Introduction

Food Waste Statistics: Food statistics offer valuable insights into the global production, consumption, distribution, and trade of food products. They cover a broad spectrum of data, including agricultural yields, food availability, nutritional consumption, price trends, and indicators of food security. Reliable and up-to-date food statistics are crucial for policymakers, industry stakeholders, and researchers to understand market trends, identify challenges in supply chains, and address issues such as hunger and malnutrition.

The significance of food statistics has increased notably in recent years, driven by factors such as the growing global population, evolving dietary habits, and the impact of climate change on agricultural output. These data points enable the monitoring of fluctuations in food demand and supply, the assessment of price instability, and the evaluation of policy impacts. Furthermore, food statistics underpin sustainable development initiatives by guiding efforts to improve food safety, minimize waste, and strengthen the resilience of global food systems.

The latest National Statistics on forestry produced by the Forestry Commission were released on 27 September 2018 according to the arrangements approved by the UK Statistics Authority. This dataset provides summary UK statistics on woodland area, planting, timber, trade, climate change, environment, recreation, employment and finance & prices as well as some statistics on international forestry. Where possible, figures are also provided for England, Wales, Scotland and Northern Ireland. More detailed statistics are published in the web publication Forestry Statistics 2018.

BioCON (Biodiversity, CO2, and Nitrogen) is an ecological experiment started in 1997 at the University of Minnesota's Cedar Creek Ecosystem Science Reserve. BioCON's goal is to explore the ways in which plant communities will respond to three environmental changes that are known to be occurring on a global scale: increasing nitrogen deposition, increasing atmospheric CO2, and decreasing biodiversity.

Why Biodiversity, CO2, and Nitrogen?

While there are many uncertainties in global change biology, there are also some well documented facts. Some of these are:

1. The amount of carbon dioxide (CO2) in the atmosphere is rising. Since the industrial revolution, the CO2 concentration in the atmosphere has increased from approximately 275 parts per million (ppm) to about 378 ppm today. This has been largely the result of fossil fuel burning. It is expected that CO2 levels will continue to rise, and that by the year 2050 these levels will be approximately 550 ppm. CO2 is the raw material for photosynthesis and is known to affect plant growth and development.

2. The amount of nitrogen moving through terrestrial ecosystems has increased in the recent past. While natural "background" levels of nitrogen fixation have remained constant, human additions to the system through fertilizer production and fossil fuel use have increased dramatically. Nitrogen is a key nutrient for plant growth and plays a critical role in plant community structure and composition in many environments.

3. Biodiversity levels are falling. While the research and data are not as complete as they are for CO2 and nitrogen, data indicate that the number of species globally, is being reduced. Perhaps more important for ecosystem function, diversity levels on local to regional scales have fallen due to land use change, biotic invasion and many other drivers.

While much is known about how each of these factors affects ecosystem functioning, many questions remain. There is also little data on how these issues affect each other, and what emergent qualities may arise when systems are exposed to these changes simultaneously. BioCON seeks to address these issues with this multi-year study at Cedar Creek Ecosytem Science Preserve.

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

The mean surface temperature change across Russia relative to the baseline from 1951 to 1980 took only positive values since 1999. The highest deviation was recorded in 2020 at 3.7 degrees Celsius. In 2023, the temperature change reached around 2.5 degrees Celsius.

Description This data set contains detailed elements of the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections for all of the p-boxes described in AR6 WG1 9.6.3 (under ar6-regional-pboxes.zip), as well as a variant excluding the AR6 estimates of background sea level change (under ar6-regional_novlm-pboxes.zip). Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool. Required Acknowledgements and Citation In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used: Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, doi:10.1017/9781009157896.011. Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. https://doi.org/10.5194/gmd-16-7461-2023 Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5281/zenodo.5914709. Please also include in the acknowledgements of works citing these projections: We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool. IPCC AR6 Licensing The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law. The development of the sea-level rise projections was supported by multiple funders, including the U.S. National Aeronautics and Space Administration (grants 80NSSC17K0698, 80NSSC20K1724 and 80NSSC21K0322 and JPL task 105393.509496.02.08.13.31), the U.S. National Science Foundation (grant ICER-1663807), the U.K. Natural Environment Research Council (grant NE/T009381/1), NIOZ Royal Netherlands Institute for Sea Research, PROTECT (which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 869304), and UK Natural Environment Research Council grant NE/T007443/1. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF.