According to a survey ran in October 2023, France had the highest share of active and casual lifestyle brand purchasers who were more concerned about the sustainability of products than they were the previous year, with over ************** of respondents making this claim. Germany had the lowest share with ** percent.

Introduction

Green Chemicals Statistics: Green chemicals, are also known as sustainable chemicals. They are produced using methods focused on minimizing environmental impact and promoting sustainability.

They are sourced from renewable materials, naturally degrade, and do not harm human health or the environment.

These chemicals are used in various sectors, such as manufacturing, agriculture, and everyday consumer products.

Their benefits include protecting the environment, and improving safety standards. Complying with regulations, and meeting the rising demand for environmentally friendly products. In conclusion, green chemicals are crucial in advancing towards an eco-friendly and sustainable future.

According to a survey conducted among consumers in the United States, ** percent of Millennial respondents said sustainability was a driving factor behind their purchasing decisions. Gen Z respondents driven by sustainability amounted to ** percent.

According to a survey conducted in 2022, around 59 percent of the C-level executives from major companies worldwide said that their firms are incorporating the use of more sustainable materials in their sustainability efforts against climate change. Another 59 percent of the executives pointed out that their companies are increasing the efficiency of energy use.

Green Data Center Market Outlook

The global green data center market size was estimated at approximately USD 53 billion in 2023, and it is projected to reach an impressive USD 145 billion by 2032, growing at a compound annual growth rate (CAGR) of around 12%. This robust growth is driven by increasing demands for energy-efficient infrastructure, coupled with heightened regulatory pressures to reduce carbon footprints across all industries. As organizations worldwide become more environmentally conscious, the adoption of green data centers is becoming an essential component of their corporate social responsibility strategies. These centers help in minimizing energy consumption and greenhouse gas emissions, while simultaneously lowering operational costs through innovative cooling solutions and sustainable energy sources.

One of the primary growth drivers for the green data center market is the escalating environmental concerns and regulatory mandates that push for energy-efficient solutions. Governments and environmental bodies across the globe have been introducing stringent regulations regarding energy consumption and carbon emissions, which has prompted organizations to shift towards sustainable data center solutions. Moreover, the rising cost of electricity and the increasing demand for data storage and processing power are encouraging companies to adopt innovative solutions that enhance energy efficiency. This trend is further fueled by advancements in technology that enable the deployment of high-performance, energy-efficient computing equipment, reducing the environmental impact of data centers.

Another significant factor contributing to the market's growth is the rapid digitization and increasing reliance on cloud services, big data, and IoT applications. As businesses continue to digitize their operations, the demand for data centers has surged, necessitating greater storage capacities and efficient data management solutions. Green data centers, with their sustainable energy usage and reduced carbon footprints, provide the ideal solution for companies looking to align their technological growth with environmental sustainability. Furthermore, the use of renewable energy resources, such as solar and wind power, is becoming increasingly common, allowing data centers to operate with minimal impact on the environment while also providing cost savings in energy expenditure.

The emergence of innovative cooling technologies, such as liquid cooling and free cooling, also plays a pivotal role in the growth of the green data center market. Traditional data centers are often burdened with high energy costs due to inefficient cooling systems. However, advances in cooling technologies have significantly reduced energy consumption, enabling data centers to operate more sustainably. Organizations are increasingly adopting these advanced solutions to optimize their energy consumption and reduce their environmental impact. Additionally, the incorporation of AI and machine learning technologies to monitor and manage data center operations has further enhanced efficiency, enabling predictive maintenance and optimizing energy usage.

Regionally, North America is expected to hold a substantial share of the green data center market, driven by early technology adoption and strong regulatory frameworks promoting sustainability. Europe follows closely, with the EU's stringent environmental policies providing a robust impetus for the development of green data centers. The Asia Pacific region is anticipated to witness the fastest growth over the forecast period, due to significant investments in IT infrastructure and increasing awareness of environmental sustainability. In contrast, the Middle East & Africa and Latin America are gradually emerging markets, with growing awareness and adoption of green practices in the data center industry, albeit at a slower pace compared to their global counterparts.

Component Analysis

The green data center market can be segmented into components comprising solutions and services. Solutions in the green data center space encompass energy-efficient infrastructure, encompassing advanced cooling technologies, energy management systems, and the integration of renewable energy sources. These solutions are designed to optimize the energy usage of data centers, thereby reducing operational costs and minimizing environmental impact. With the need for sustainable practices becoming more urgent, organizations are increasingly investing in these solutions to align with their corporate responsibility goals. The solutions segment is witnessing rapid technological advancements, with the devel

The 2005 Environmental Sustainability Index (ESI) is a measure of overall progress towards environmental sustainability, developed for 146 countries. The index provides a composite profile of national environmental stewardship based on a compilation of 21 indicators derived from 76 underlying data sets. The 2005 version of the ESI represents a significant update and improvement on earlier versions; the country ESI scores or rankings should not be compared to earlier versions because of changes to the methodology and underlying data. The index was unveiled at the World Economic Forum's annual meeting, January 2005, Davos, Switzerland. The 2005 ESI is a joint product of the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN), in collaboration with the World Economic Forum (WEF) and the Joint Research Centre (JRC), European Commission.

The dataset, titled AI Sustainability Dataset, contains 24 records detailing various AI applications in sustainability-related areas such as environmental monitoring, energy efficiency, disaster prediction, and climate modeling. Each record includes an AI application’s description along with key metrics such as impact score (1-10), efficiency improvement percentage, resource savings (metric tons), cost reduction (million dollars), carbon footprint reduction (CO2 tons), AI adoption rate, implementation cost, return on investment (ROI in years), automation level, public awareness score, and regulatory support level. The data quantifies the effectiveness of AI solutions in reducing environmental impact, improving efficiency, and saving costs, offering insights into AI's role in sustainable development. ​

The Ancillary Data portion of the Compendium of Environmental Sustainability Indicator Collections contains 38 variables (time series data on population and gross domestic product as well as region codes, land area, and waterbody area) for 238 countries. The data are taken from the UN Population Division, the World Bank, the CIA Factbook, and CIESIN's Gridded Population of the World, and are distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

Learn how industry research empowers businesses to turn sustainability challenges into opportunities, driving growth, efficiency and lasting impact.

The Greater China area, including the territories of Taiwan and Hong Kong, is the most advanced user of artificial intelligence (AI) in their efforts for sustainability, with ** percent of organizational respondants responding positively. North-America is the least developed in using AI for sustainability purpose, with less than ******* of companies there using AI in their sustainability efforts.

Replication Data for the published paper 'Going green: Framing effects in a dynamic coordination game'. Decision-making in a (novel) dynamic coordination game that simulates ‘social tipping’ is studied. In the experiment, the game is repeated five times, which enables groups to learn to coordinate. A neutral language treatment is compared with a ‘green framing’ treatment, in which meaningful context is added to the instructions. Findings reveal that green framing significantly increases the number of successful transitions, but also reduces the group's ability to coordinate in subsequent games. Consequently, while green framing results in twice as many transitions, these are also more costly such that payoffs do not differ between treatments. In the context of environmental policy, the experiment suggests general support for ‘going green’, but it also points to green framing causing proponents and opponents to stick to their strategies reducing potential gains from coordination between proponents and opponents of environmentally friendly actions. [Description is based on the article's abstract]

With consumers placing increasing importance on companies’ environmental credentials, what are UK retailers doing to make their operations more sustainable?

This data set lists sustainability metric data for state-owned buildings. These data are used to track state departments’ progress toward the goals mandated in Executive Order B-18-12. The metrics tracked in this set are total water use, total energy use, renewable energy generation and LEED certifications. The data set also includes building information for the 1722 buildings listed including, building name, address, total square footage and use type. These data are entered by property owners from each state department into the database Energy Star Portfolio Manager. Most data are obtained by property owner using the utility bill; however, some of the information is automatically fed into the database by the utility company.

Note: Find data at source. ・ The goal of the Smart* project is to optimize home energy consumption. Available here is a wide variety of data collected from three real homes, including electrical (usage and generation), environmental (e.g., temperature and humidity), and operational (e.g., wall switch events). Also available is minute-level electricity usage data from 400+ anonymous homes.

The Compendium of Environmental Sustainability Indicator Collections, Version 1.1 contains 426 indicators for 239 countries from five major environmental sustainability indicator efforts: the 2006 Environmental Performance Index (EPI), 2005 Environmental Sustainability Index (ESI), 2004 Environmental Vulnerability Index (EVI), the Rio to Johannesburg Dashboard, the Wellbeing of Nations, and 2006 National Footprint Accounts. It also incorporates 38 ancillary variables such as region name, dummy variables for landlocked countries and small island states, population, GDP, and land area. The collection is compiled and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The zip file linked contains three subdirectories and a parameter list to be used for processing using ACCEPT. Datafiles are partitioned into training, validation, and testing sub-directory structures. A text file contains all parameter identifiers associated with the cold complaint prediction scenario. Please note that the parameter list is a text file containing the following lines: DC114T - Electrical room temperature DCRCS103 - Carbon Dioxide concentration sensor in first floor conference room DCTN240T - Second floor conference room temperature Please note that Appendix E of an accompanying technical report will be posted here shortly, which will provide more detail on the cold complaint scenario, along with step-by-step directions on how to reproduce the results for this example using ACCEPT. Other appendices will provide detailed set up and configuration instructions. Here is the citation: Rodney Martin, Santanu Das, Vijay Janakiraman, Stefan Hosein. ACCEPT: Introduction of the Adverse Condition and Critical Event Prediction Toolbox, NASA Technical Report, NASA/TM–2015– 218927, November 2015.

LCA/LCCA/LCIA data used to create figures and tables in the papers. This dataset is associated with the following publications: Ghimire, S., and J. Johnston. Holistic impact assessment and cost savings of rainwater harvesting at the watershed scale. Elementa: Science of the Anthropocene. University of California Press (UC Press), Oakland, CA, USA, 5(9): 1-17, (2017). Ghimire, S., and J. Johnston. A modified eco-efficiency framework and methodology for advancing the state of practice of sustainability analysis as applied to green infrastructure. Integrated Environmental Assessment and Management. Allen Press, Inc., Lawrence, KS, USA, 13(5): 821-831, (2017). Ghimire, S., J. Johnston, W. Ingwersen, and S. Sojka. Life cycle assessment of a commercial rainwater harvesting system compared with a municipal water supply system. JOURNAL OF CLEANER PRODUCTION. Elsevier Science Ltd, New York, NY, USA, 151: 74–86, (2017).

The data and programs replicate tables and figures from "Going Green in China: Firms' Responses to Stricter Environmental Regulations", by Fan, Graff Zivin, Kou, Liu, and Wang. Please see the ReadMe file for additional details.

Develop Louisville Focuses on the full range of land development activities, including planning and design, vacant property initiatives, advanced planning, housing & community development programs, permits and licensing, land acquisition, public art and clean and green sustainable development partnerships.

Go Green Oklahoma is an OK.gov initiative showcasing how Oklahoma eGovernment is helping to reduce the carbon footprint by reducing paper consumption and citizen travel to government facilities. Currently, the 'Go Green Oklahoma' study provides data from online services provided by the state of Oklahoma. We invite state agencies to report their online services that reduce paper consumption and/or carbon emissions, to be included in our dataset. The data consists of conservative estimates limited to the date ranges of January 2007–December 2010.