According to the Kärcher cleaning study of 2019, Brazilian respondents living in the country's Northeast region registered the highest share of people who consider having a clean home as very important. Also, none of respondents from that region showed an indifferent opinion on this topic. Brazilians respondents from the South region tended towards a more flexible attitude towards the cleanliness of their homes, with 76 percent considering it very important, somewhat important for another 20 percent, and partly important, partly unimportant for the remaining four percent .

This clean dataset is a refined version of our company datasets, consisting of 35M+ data records.

It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B data. After cleaning, this data is also enriched by leveraging a carefully instructed large language model (LLM).

AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

Coresignal is a leading public business data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

This statistic shows the results of a survey conducted in the United States in 2017 on the importance of ecofriendly seals on cleaning products. Some 55 percent of respondents stated they sometimes look out for ecofriendly seals on cleaning products. The Survey Data Table for the Statista survey Cleaning Products in the United States 2018 contains the complete tables for the survey including various column headings.

Graph and download economic data for Relative Importance Weights: Manufacturing: Nondurable Goods: Soap, Cleaning Compound, and Toilet Preparation (NAICS = 3256) (RIWG3256S) from Jan 1972 to Feb 2025 about hygiene, cleaning, contributions, chemicals, IP, production, industry, indexes, and USA.

This statistic presents data on the importance of a clean user interface on streaming music services according to consumers in the United States as of March 2018. During the survey, 38 percent of the respondents stated that having a clean user interface on streaming music services was very important.

Snapshot img

Cleaning Services Market Size and Trends

The cleaning services market size is forecast to increase by USD 21.78 billion, at a CAGR of 6.4% between 2023 and 2028. Market growth depends on rising health concerns in workplaces, which are notably driving demand for solutions that enhance employee well-being. A key trend shaping the market is strong residential growth, as more individuals seek healthy living environments that support overall wellness. However, the cleaning service market also faces significant challenges, particularly the lack of skilled labor, which hinders the ability to meet the increasing demand for health-focused products and services. Effectively addressing this skills gap while capitalizing on health-conscious trends will be essential for companies aiming to thrive in this competitive landscape.

Request Free Sample

The market caters to both residential and commercial customers, encompassing various sectors such as office buildings, retail stores, healthcare facilities, and more. Services offered include window washing, floor cleaning, vacuuming, furniture cleaning, contract cleaning, carpet cleaning, air duct cleaning, and water damage restoration. With the economic upturn, business entities have been prioritizing workplace hygiene and sustainability, leading to an increase in demand for these services. Dual-income households and working parents also value the convenience and efficiency of professional cleaning services. High competition among cleaning companies necessitates strict adherence to safety protocols and effective operations. Real estate investment properties also require regular cleaning to maintain their value. Building workers and janitors play a crucial role in ensuring the cleanliness and upkeep of these spaces. Overall, the market is a significant contributor to workplace wellness and business success.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion ' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

End-user Outlook

  North America
  Europe
  APAC
  South America
  Middle East and Africa


Region Outlook

  North America

    Chile
    Brazil
    Argentina


  South America

    The U.S.
    Canada





  Europe

    U.K.
    Germany
    France
    Rest of Europe





  APAC

    China
    India





  Middle East & Africa

    Saudi Arabia
    South Africa
    Rest of the Middle East & Africa

By End-user Insights

The commercial segment is estimated to witness significant growth during the forecast period. The market encompasses various aspects of maintaining hygiene and sustainability in both commercial and residential settings. Key services include window washing, floor cleaning, vacuum cleaning, furniture cleaning, carpet cleaning, air duct cleaning, and water damage restoration. Commercial customers, such as business entities, office buildings, retail stores, and healthcare facilities, prioritize workplace hygiene and sustainability for employee wellness and adherence to health restrictions. The economic upturn and increased discretionary income in dual-income households fuel the demand for these services. Residential customers also value cleaning priorities, particularly in light of safety protocols and the aging population's need for assistance. High competition in the market drives innovation, with eco-friendly products and advanced disinfection techniques becoming increasingly popular.

Get a glance at the market share of various regions Download the PDF Sample

The commercial segment was the largest and was valued at USD 40.05 billion in 2018. Rapid urbanization and the growing importance of workplace sustainability further contribute to the market's growth. Cleaning Authority, Cleannet, and other leading companies offer a range of services, from daily operations to special projects. Building workers, janitors, and other professionals ensure the smooth execution of cleaning tasks in various settings, including schools, colleges, universities, laboratories, and spas and salons. The market caters to diverse needs, from the hospitality industry's focus on guest comfort to the healthcare sector's stringent cleanliness standards. In conclusion, the market plays a crucial role in maintaining hygiene, promoting workplace sustainability, and ensuring employee and public health. It caters to the needs of both commercial and residential customers, employing various techniques and eco-friendly products to meet the evolving demands of modern society.

Regional Analysis

For more insights on the market share of various regions Download PDF Sample now!

APAC is estimated to contribute 39% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and

The Data Cleansing Tools market is rapidly evolving as businesses increasingly recognize the importance of data quality in driving decision-making and strategic initiatives. Data cleansing, also known as data scrubbing or data cleaning, involves the process of identifying and correcting errors and inconsistencies in

Clean Transportation Program Data 2022. The Clean Transportation Program (also known as Alternative and Renewable Fuel and Vehicle Technology Program) invests up to $100 million annually in a broad portfolio of transportation and fuel transportation projects throughout the state. The Energy Commission leverages public and private investments to support adoption of cleaner transportation powered by alternative and renewable fuels. The program plays an important role in achieving California’s ambitious goals on climate change, petroleum reduction, and adoption of zero-emission vehicles, as well as efforts to reach air quality standards. The program also supports the state’s sustainable, long-term economic development.Data within this application was last updated August 2024.For more information on the Clean Transportation Program, visit:https://www.energy.ca.gov/programs-and-topics/programs/clean-transportation-program

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The survey data covers urban, rural and camp areas in West Bank and Gaza Strip.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered all Palestinian households who are usually resident in the Palestinian Territory during 2010.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The sampling frame consists of all enumeration areas which were enumerated in 2007, each numeration area consists of buildings and housing units with average of about 120 households in it. These enumeration areas are used as primary sampling units PSUs in the first stage of the sampling selection.

Sample Design:

The sample is a stratified cluster systematic random sample with two stages: First stage: selection of a systematic random sample of 192 enumeration areas. Second stage: selection of a systematic random sample of 24 households from each enumeration area selected in the first stage.

Note: in Jerusalem Governorate (J1), 13 enumeration areas were selected; then in the second phase, a group of households from each enumeration area were chosen using census-2007 method of delineation and enumeration. This method was adopted to ensure household response is to the maximum to comply with the percentage of non-response as set in the sample design.Enumeration areas were distributed to twelve months and the sample for each quarter covers sample strata (Governorate, locality type) Sample strata:

The population was divided by:

1- Governorate 2- Type of Locality (urban, rural, refugee camps)

Sample Size:

The calculated sample size for the Expenditure and Consumption Survey in 2010 is about 3,757 households, 2,574 households in West Bank and 1,183 households in Gaza Strip.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire consists of two main parts:

First: Survey's questionnaire

Part of the questionnaire is to be filled in during the visit at the beginning of the month, while the other part is to be filled in at the end of the month. The questionnaire includes:

Control sheet: Includes household’s identification data, date of visit, data on the fieldwork and data processing team, and summary of household’s members by gender.

Household roster: Includes demographic, social, and economic characteristics of household’s members.

Housing characteristics: Includes data like type of housing unit, number of rooms, value of rent, and connection of housing unit to basic services like water, electricity and sewage. In addition, data in this section includes source of energy used for cooking and heating, distance of housing unit from transportation, education, and health centers, and sources of income generation like ownership of farm land or animals.

Food and Non-Food Items: includes food and non-food items, and household record her expenditure for one month.

Durable Goods Schedule: Includes list of main goods like washing machine, refrigerator,TV.

Assistances and Poverty: Includes data about cash and in kind assistances (assistance value,assistance source), also collecting data about household situation, and the procedures to cover expenses.

Monthly and annual income: Data pertinent to household’s income from different sources is collected at the end of the registration period.

Second: List of goods

The classification of the list of goods is based on the recommendation of the United Nations for the SNA under the name Classification of Personal Consumption by purpose. The list includes 55 groups of expenditure and consumption where each is given a sequence number based on its importance to the household starting with food goods, clothing groups, housing, medical treatment, transportation and communication, and lastly durable goods. Each group consists of important goods. The total number of goods in all groups amounted to 667 items for goods and services. Groups from 1-21 includes goods pertinent to food, drinks and cigarettes. Group 22 includes goods that are home produced and consumed by the household. The groups 23-45 include all items except food, drinks and cigarettes. The groups 50-55 include durable goods. The data is collected based on different reference periods to represent expenditure during the whole year except for cars where data is collected for the last three years.

Registration form

The registration form includes instructions and examples on how to record consumption and expenditure items. The form includes columns: 1.Monetary: If the good is purchased, or in kind: if the item is self produced. 2.Title of the service of the good 3.Unit of measurement (kilogram, liter, number) 4. Quantity 5. Value

The pages of the registration form are colored differently for the weeks of the month. The footer for each page includes remarks that encourage households to participate in the survey. The following are instructions that illustrate the nature of the items that should be recorded: 1. Monetary expenditures during purchases 2. Purchases based on debts 3.Monetary gifts once presented 4. Interest at pay 5. Self produced food and goods once consumed 6. Food and merchandise from commercial project once consumed 7. Merchandises once received as a wage or part of a wage from the employer.

Cleaning operations

Raw Data

Data editing took place through a number of stages, including: 1. Office editing and coding 2. Data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consisted of 4,767 households, which includes 4,608 households of the original sample plus 159 households as an additional sample. A total of 3,757 households completed the interview: 2,574 households from the West Bank and 1,183 households in the Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the Palestinian Territory 28.1% (82.4% in the West Bank was and 81.6% in Gaza Strip).

Sampling error estimates

The impact of errors on data quality was reduced to a minimum due to the high efficiency and outstanding selection, training, and performance of the fieldworkers. Procedures adopted during the fieldwork of the survey were considered a necessity to ensure the collection of accurate data, notably: 1) Develop schedules to conduct field visits to households during survey fieldwork. The objectives of the visits and the data collected on each visit were predetermined. 2) Fieldwork editing rules were applied during the data collection to ensure corrections were implemented before the end of fieldwork activities. 3) Fieldworkers were instructed to provide details in cases of extreme expenditure or consumption by the household. 4) Questions on income were postponed until the final visit at the end of the month. 5) Validation rules were embedded in the data processing systems, along with procedures to verify data entry and data edit.

Snapshot img

Medical Device Cleaning Market Size 2025-2029

The medical device cleaning market size is forecast to increase by USD 750.4 million and is estimated to grow at a CAGR of 5.6% between 2024 and 2029.

The market is experiencing significant growth due to the increasing importance of infection control in healthcare settings. With the prevalence of healthcare-associated infections (HAIs) continuing to pose a major challenge, there is a heightened focus on implementing effective sanitization and sterilization processes for medical devices. 3M, a leading company, offers medical device cleaning products such as 3M glutarex 1L, 3M glutarex 5L, and 3M radpid multi enzyme cleaner 70500 1L.
As healthcare facilities strive to reduce their carbon footprint and minimize waste, there is a push for eco-friendly alternatives to traditional cleaning agents. However, the lack of standardized cleaning protocols across healthcare facilities presents a challenge, as each facility may have unique requirements and preferences. The market is driven by the need to prevent HAIs and ensure infection control in healthcare settings. Infection control policies mandate stringent cleaning and disinfection procedures for critical devices like endoscopes and surgical instruments.

What will be the size of Market during the forecast period?

Request Free Market Sample

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments.

Device

  Semi-critical
  Critical
  Non-critical


Technique

  Disinfection
  Sterilization
  Cleaning
  Others


EPA Classification

  High Level
  Intermediate Level
  Low Level


Geography

  North America

    Canada
    US


  Asia

    China
    India
    Japan
    South Korea


  Europe

    Germany
    UK
    France
    Italy


  Rest of World (ROW)

Which is the largest segment driving market growth?

The semi-critical segment is estimated to witness significant growth during the forecast period. The market is experiencing growth due to the increasing importance of semi-critical devices, such as ultrasonic cleaners, washer-disinfectors, and sterilization equipment. These devices, which contact mucous membranes or damaged skin, require thorough cleaning to prevent infection spread. The significance of infection control procedures and heightened awareness of healthcare-associated infections are driving the expansion of the semi-critical equipment market.

Get a glance at the market share of various regions. Download the PDF Sample

The semi-critical segment was the largest segment and valued at USD 962.90 million in 2019. Strict regulations and laws, including the Centers for Disease Control and Prevention (CDC) Guideline for Disinfection and Sterilization in Healthcare Facilities, further emphasize the importance of properly cleaning and disinfecting medical equipment. Collaborations between industry players and healthcare institutions are also on the rise to ensure the highest standards of cleanliness for critical devices. The market outlook for medical device cleaning solutions remains positive as the demand for effective and efficient cleaning methods continues to increase. Hence, such factors are fuelling the growth of this segment during the forecast period.

Which region is leading the market?

For more insights on the market share of various regions, Request Free Sample

North America is estimated to contribute 38% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. In North America, the market is experiencing significant growth due to the increasing incidence of healthcare-associated infections (HAIs) and the heightened emphasis on infection control. This market caters to the demand for effective and efficient cleaning solutions for medical devices. The medical device cleaning market is driven by the increasing focus on non-critical, semi-critical, and critical device cleanliness. Automated cleaning systems are widely adopted, ensuring effective disinfection protocols and high-level disinfection of reusable medical devices. Key considerations include surface contamination control and endoscope cleaning, which require rigorous cleaning validation to maintain regulatory compliance and ensure patient safety in healthcare environments.

The use of specialized cleaning solutions for semi-critical devices is crucial for surgical operations. The trend towards sustainable cleaning solutions offers opportunities for innovation, while the lack of standardization presents a challenge that must be addressed to ensure consistent and effective cleaning processes. The North American ma

Data were collected through structured interviews and observations during summer 2019 and through 2020. Processing included data cleaning and wrangling (non reproducible code available online), anonymization of identifiable information and dataset restructuring.

Recent developments include: January 2022: IBM and Francisco Partners disclosed the execution of a definitive contract under which Francisco Partners will purchase medical care information and analytics resources from IBM, which are currently part of the IBM Watson Health business., October 2021: Informatica LLC announced an important cloud storage agreement with Google Cloud in October 2021. This collaboration allows Informatica clients to transition to Google Cloud as much as twelve times quicker. Informatica's Google Cloud Marketplace transactable solutions now incorporate Master Data Administration and Data Governance capabilities., Completing a unit of labor with incorrect data costs ten times more estimates than the Harvard Business Review, and finding the correct data for effective tools has never been difficult. A reliable system may be implemented by selecting and deploying intelligent workflow-driven, self-service options tools for data quality with inbuilt quality controls.. Key drivers for this market are: Increasing demand for data quality: Businesses are increasingly recognizing the importance of data quality for decision-making and operational efficiency. This is driving demand for data quality tools that can automate and streamline the data cleansing and validation process.

Growing adoption of cloud-based data quality tools: Cloud-based data quality tools offer several advantages over on-premises solutions, including scalability, flexibility, and cost-effectiveness. This is driving the adoption of cloud-based data quality tools across all industries.

Emergence of AI-powered data quality tools: AI-powered data quality tools can automate many of the tasks involved in data cleansing and validation, making it easier and faster to achieve high-quality data. This is driving the adoption of AI-powered data quality tools across all industries.. Potential restraints include: Data privacy and security concerns: Data privacy and security regulations are becoming increasingly stringent, which can make it difficult for businesses to implement data quality initiatives.

Lack of skilled professionals: There is a shortage of skilled data quality professionals who can implement and manage data quality tools. This can make it difficult for businesses to achieve high-quality data.

Cost of data quality tools: Data quality tools can be expensive, especially for large businesses with complex data environments. This can make it difficult for businesses to justify the investment in data quality tools.. Notable trends are: Adoption of AI-powered data quality tools: AI-powered data quality tools are becoming increasingly popular, as they can automate many of the tasks involved in data cleansing and validation. This makes it easier and faster to achieve high-quality data.

Growth of cloud-based data quality tools: Cloud-based data quality tools are becoming increasingly popular, as they offer several advantages over on-premises solutions, including scalability, flexibility, and cost-effectiveness.

Focus on data privacy and security: Data quality tools are increasingly being used to help businesses comply with data privacy and security regulations. This is driving the development of new data quality tools that can help businesses protect their data..

Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demograohic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor chracteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Household Expenditure and Income Survey sample was designed using two-stage cluster stratified sampling method. In the first stage, the primary sampling units (PSUs), the blocks, were drawn using probability proportionate to the size, through considering the number of households in each block to be the block size. The second stage included drawing the household sample (8 households from each PSU) using the systematic sampling method. Fourth substitute households from each PSU were drawn, using the systematic sampling method, to be used on the first visit to the block in case that any of the main sample households was not visited for any reason.

To estimate the sample size, the coefficient of variation and design effect in each subdistrict were calculated for the expenditure variable from data of the 2006 Household Expenditure and Income Survey. This results was used to estimate the sample size at sub-district level, provided that the coefficient of variation of the expenditure variable at the sub-district level did not exceed 10%, with a minimum number of clusters that should not be less than 6 at the district level, that is to ensure good clusters representation in the administrative areas to enable drawing poverty pockets.

It is worth mentioning that the expected non-response in addition to areas where poor families are concentrated in the major cities were taken into consideration in designing the sample. Therefore, a larger sample size was taken from these areas compared to other ones, in order to help in reaching the poverty pockets and covering them.

Mode of data collection

Face-to-face [f2f]

Research instrument

List of survey questionnaires: (1) General Form (2) Expenditure on food commodities Form (3) Expenditure on non-food commodities Form

Cleaning operations

Raw Data The design and implementation of this survey procedures were: 1. Sample design and selection 2. Design of forms/questionnaires, guidelines to assist in filling out the questionnaires, and preparing instruction manuals 3. Design the tables template to be used for the dissemination of the survey results 4. Preparation of the fieldwork phase including printing forms/questionnaires, instruction manuals, data collection instructions, data checking instructions and codebooks 5. Selection and training of survey staff to collect data and run required data checkings 6. Preparation and implementation of the pretest phase for the survey designed to test and develop forms/questionnaires, instructions and software programs required for data processing and production of survey results 7. Data collection 8. Data checking and coding 9. Data entry 10. Data cleaning using data validation programs 11. Data accuracy and consistency checks 12. Data tabulation and preliminary results 13. Preparation of the final report and dissemination of final results

Harmonized Data - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets - The harmonization process started with cleaning all raw data files received from the Statistical Office - Cleaned data files were then all merged to produce one data file on the individual level containing all variables subject to harmonization - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables - A post-harmonization cleaning process was run on the data - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format

Market Overview The global Underwear Cleaning Fluid market is anticipated to attain a notable market size, growing at a substantial CAGR over the estimated period 2025-2033. In terms of value, the market is estimated to expand from million in 2025 to million by 2033. The growth of the market is attributed to increasing health awareness, urbanization, and rising disposable incomes. Additionally, the growing preference for automated and convenient cleaning methods is further driving market demand. Key Drivers and Restraints One of the major drivers of the Underwear Cleaning Fluid market is the increasing awareness about the importance of intimate hygiene. This is due to the growing prevalence of infections and diseases caused by poor intimate hygiene. Another factor that is contributing to the market growth is the rising urbanization and changing lifestyles. With increasing urbanization, people are becoming more aware of the importance of personal hygiene and are seeking out products that can help them maintain a healthy lifestyle. However, the high cost of underwear cleaning fluids and the availability of substitutes may pose challenges to the growth of the market.

Abstract

The primary objective of the 2006 DHS is to provide to the Department of Health (DOH), Department of National Planning and Monitoring (DNPM) and other relevant institutions and users with updated and reliable data on infant and child mortality, fertility preferences, family planning behavior, maternal mortality, utilization of maternal and child health services, knowledge of HIV/AIDS and behavior, sexually risk behavior and information on the general household amenities. This information contributes to policy planning, monitoring, and program evaluation for development at all levels of government particularly at the national and provincial levels. The information will also be used to assess the performance of government development interventions aimed at addressing the targets set out under the MDG and MTDS. The long-term objective of the survey is to technically strengthen the capacity of the NSO in conducting and analyzing the results of future surveys.

The successful conduct and completion of this survey is a result of the combined effort of individuals and institutions particularly in their participation and cooperation in the Users Advisory Committee (UAC) and the National Steering Committee (NSC) in the different phases of the survey.

The survey was conducted by the Population and Social Statistics Division of the National Statistical Office of PNG. The 2006 DHS was jointly funded by the Government of PNG and Donor Partners through ADB while technical assistance was provided by International Consultants and NSO Philippines.

Geographic coverage

National level Regional level Urban and Rural

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure household members (usual residents), all women and men aged 15-50 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary focus of the 2006 DHS is to provide estimates of key population and health indicators at the national level. A secondary but important priority is to also provide estimates at the regional level, and for urban and rural areas respectively. The 2006 DHS employed the same survey methodology used in the 1996 DHS. The 2006 DHS sample was a two stage self-weighting systematic cluster sample of regions with the first stage being at the census unit level and the second stage at the household level. The 2000 Census frame comprised of a list of census units was used to select the sample of 10,000 households for the 2006 DHS.

A total of 667 clusters were selected from the four regions. All census units were listed in a geographic order within their districts, and districts within each province and the sample was selected accordingly through the use of appropriate sampling fraction. The distribution of households according to urban-rural sectors was as follows:

8,000 households were allocated to the rural areas of PNG. The proportional allocation was used to allocate the first 4,000 households to regions based on projected citizen household population in 2006. The other 4,000 households were allocated equally across all four regions to ensure that each region have sufficient sample for regional level analysis.

2,000 households were allocated to the urban areas of PNG using proportional allocation based on the 2006 projected urban citizen population. This allocation was to ensure that the most accurate estimates for urban areas are obtained at the national level.

All households in the selected census units were listed in a separate field operation from June to July 2006. From the list of households, 16 households were selected in the rural census units and 12 in the urban census units using systematic sampling. All women and men age 15-50 years who were either usual residents of the selected households or visitors present in the household on the night before the survey were eligible to be interviewed. Further information on the survey design is contained in Appendix A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the 2006 DHS namely; the Household Questionnaire (HHQ), the Female Individual Questionnaire (FIQ) and the Male Individual Questionnaire (MIQ). The planning and development of these questionnaires involved close consultation with the UAC members comprising of the following line departments and agencies namely; Department of Health (DOH), Department of Education (DOE), Department of National Planning and Monitoring (DNPM), National Aids Council Secretariat (NACS), Department of Agriculture and Livestock (DAL), Department of Labour and Employment (DLE), University of Papua New Guinea (UPNG), National Research Institute (NRI) and representatives from Development partners.

The HHQ was designed to collect background information for all members of the selected households. This information was used to identify eligible female and male respondents for the respective individual questionnaires. Additional information on household amenities and services, and malaria prevention was also collected.

The FIQ contains questions on respondents background, including marriage and polygyny; birth history, maternal and child health, knowledge and use of contraception, fertility preferences, HIV/AIDS including new modules on sexual risk behaviour and attitudes to issues of well being. All females age 15-50 years identified from the HHQ were eligible for interview using this questionnaire.

The MIQ collected almost the same information as in the FIQ except for birth history. All males age 15-50 years identified from the HHQ were eligible to be interviewed using the MIQ.

Two pre-tests were carried out aimed at testing the flow of the existing and new questions and the administering of the MIQ between March and April 2006. The final questionnaires contained all the modules used in the 1996 DHS including new modules on malaria prevention, sexual risk behaviour and attitudes to issues of well being.

Cleaning operations

All questionnaires from the field were sent to the NSO headquarters in Port Moresby in February 2007 for editing and coding, data entry and data cleaning. Editing was done in 3 stages to enable the creation of clean data files for each province from which the tabulations were generated. Data entry and processing were done using the CSPro software and was completed by October 2008.

Response rate

Table A.2 of the survey report provides a summary of the sample implementation of the 2006 DHS. Despite the recency of the household listing, approximately 7 per cent of households could not be contacted due to prolonged absence or because their dwellings were vacant or had been destroyed. Among the households contacted, a response rate of 97 per cent was achieved. Within the 9,017 households successfully interviewed, a total of 11, 456 women and 11, 463 of men age 15-49 years were eligible to be interviewed. Successful interviews were conducted with 90 per cent of eligible women (10, 353) and 88 per cent of eligible men (10,077). The most common cause of non-response was absence (5 per cent). Among the regions, the rate of success among women was highest in all the regions (92 per cent each) except for Momase region at 86 per cent. The rate of success among men was highest in Highlands and Islands region and lowest in Momase region. The overall response rate, calculated as the product of the household and female individual response rate (.97*.90) was 87 per cent.

Sampling error estimates

Appendix B of the survey report describes the general procedure in the computation of sampling errors of the sample survey estimates generated. It basically follows the procedure adopted in most Demographic and Health Surveys.

Data appraisal

Appendix C explains to the data users the quality of the 2006 DHS. Non-sampling errors are those that occur in surveys and censuses through the following causes: a) Failure to locate the selected household b) Mistakes in the way questions were asked c) Misunderstanding by the interviewer or respondent d) Coding errors e) Data entry errors, etc.

Total eradication of non-sampling errors is impossible however great measures were taken to minimize them as much as possible. These measures included: a) Careful questionnaire design b) Pretesting of survey instruments to guarantee their functionality c) A month of interviewers’ and supervisors’ training d) Careful fieldwork supervision including field visits by NSOHQ personnel e) A swift data processing prior to data entry f ) The use of interactive data entry software to minimize errors

Snapshot img

US Commercial and Residential Cleaning Services Market Size 2025-2029

The US commercial and residential cleaning services market size is forecast to increase by USD 37.8 billion at a CAGR of 5.9% between 2024 and 2029.

The demand for cleaning services in the US is experiencing significant growth due to several key trends. The increasing popularity of multifamily dwellings is driving market expansion, as the demand for professional cleaning services in large apartment complexes continues to rise. Furthermore, strategic alliances between cleaning service providers and providers of property management are becoming more common, enabling both parties to benefit from economies of scale and improved operational efficiency. Another factor influencing market growth is the fluctuation in labor wages. While higher wages can increase operating costs for cleaning companies, they also help to ensure a skilled and motivated workforce, leading to better service quality and customer satisfaction. Overall, these trends are expected to continue shaping the market.

What will be the Size of the market During the Forecast Period?

Request Free Sample

The commercial and residential cleaning services market encompasses a range of cleaning processes designed to maintain hygiene and promote health in various facility types. General cleaning duties include the use of specialized cleaning techniques and methods for both commercial and residential properties Services cater to offices, cleanrooms, medical facilities, and healthcare facilities, adhering to stringent sanitary requirements. Residential cleaning services focus on maintaining the cleanliness and order of homes. Cleaning companies employ trained cleaners equipped with advanced cleaning equipment and supplies to deliver efficient and effective cleaning solutions.
Furthermore, deep cleaning, sanitizing, and disinfection are essential components of commercial cleaning services, ensuring a healthy work environment. Customer experience is a critical differentiator, with companies prioritizing foreman pro cleaning and specialized technology to enhance service delivery. Industrial cleaning involves the application of heavy-duty cleaning methods and equipment to large-scale facilities. Cleaning standards continue to evolve, with an increasing focus on sustainability and eco-friendly cleaning practices. The market is expected to grow, driven by the need for cleaner and healthier environments, as well as the availability of advanced cleaning technologies.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Sector

  Commercial
  Residential


Service Type

  Janitorial services
  Carpet and upholstery cleaning services
  Outdoor areas
  Others


Technique

  Traditional techniques
  Eco-friendly techniques


Geography

  US

By Sector Insights

The commercial segment is estimated to witness significant growth during the forecast period. The commercial segment of the cleaning services market In the US encompasses various end-users, including hospitality establishments, spas and salons, food service industries, hospitals and healthcare centers, institutions, and offices. Among these, commercial office buildings and healthcare organizations are projected to drive significant growth In the market. The healthcare sector's demand is particularly high due to stringent government regulations mandating cleanliness in healthcare establishments.

Furthermore, the market In the US is expected to expand at a notable rate during the forecast period, fueled by the increasing recognition of the importance of cleanliness and hygiene in commercial settings. Cleaning services encompass general cleaning, deep cleaning, sanitizing, and disinfection. Cleaning equipment, standards, and supplies are essential components of these services. The natural cleaning supplies trend is gaining popularity due to environmental concerns and health benefits.

Get a glance at the share of various segments Request Free Sample

Market Dynamics

Our US Commercial And Residential Cleaning Services Market researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers for the US Commercial and Residential Cleaning Services Market?

The rising popularity of multifamily dwellings in US is the key driver of the market. The market In the US has witnessed significant growth due to the increasing demand for clean and hygienic environments, particularly In the wake of the COVID-19 pandemic. Cleaning processes, techniq

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

BRIEF FACE-TO-FACE

The metropolitan, urban and rural population and all .administrative regional units. as defined in Official Europe Union Statistics (NUTS 2) covered proportionately the respective population aged 18 and above. The country was divided into an appropriate number of areas, grouping NUTS regions at whatever level appropriately.

The NUTS covered in the Netherlands were the following; Drente, Flevoland, Friesland, Gelderland, Gröningen, Limburg, Noord-Brabant, Noord-Holland, Overijssel, Utrecht, Zeeland, Zuid-Holland.

The basic sample design was a multi-stage, random probability sample. 100 sampling points were drawn with probability proportional to population size, for a total coverage of the country. The sampling points were drawn after stratification by NUTS 2 region and by degree of urbanisation. They represented the whole territory of the country surveyed and are selected proportionally to the distribution of the population in terms of metropolitan, urban and rural areas. In each of the selected sampling points, one address was drawn at random. This starting address forms the first address of a cluster of a maximum of 20 addresses. The remainder of the cluster was selected as every Nth address by standard random route procedure from the initial address. In theory, there is no maximum number of addresses issued per country. Procedures for random household selection and random respondent selection are independent of the interviewer.s decision and controlled by the institute responsible. They should be as identical as possible from to country, full functional equivalence being a must.

At every address up to 4 recalls were made to attempt to achieve an interview with the selected respondent. There was only one interview per household. The final sample size is 1,085 completed interviews.

POSTAL

The Municipal Population Registry (GBA) was used to select a representative sample of 3,000 individuals, aged 18 and over, of the Dutch population. Municipals were selected first and then the individual sample was drawn up.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

According to Cognitive Market Research, The Global Fiber Inspection And Cleaning market size is USD XX billion in 2023 and will expand at a CAGR of 5.60% from 2023 to 2030.

The demand for Fiber Inspection and Cleaning is rising due to the numerous strategies adopted by key participants.
Demand for dry cleaning techniques remains higher in the Fiber Inspection and Cleaning market.
The connector inspection category held the highest Fiber Inspection and Cleaning market revenue share in 2023.
North American Fiber Inspection and Cleaning will continue to lead, whereas the European Fiber Inspection and Cleaning market will experience the most substantial growth until 2030.

Growing Demand for High-speed Data Transmission to Provide Viable Market Output

The increased reliance on the internet, as well as the expansion of bandwidth-intensive applications like as streaming and cloud computing, have increased the demand for fast and dependable data transmission networks. As a result of this demand, fiber optic cables have emerged as the preferred alternative, enabling exceptional data transmission capability over long distances. Fiber optics offer effective communication due to their capacity to carry massive amounts of data quickly, making them the ideal choice for high-speed networks. As technology progresses and data consumption grows, fiber optic cables stand out as a critical enabler, fulfilling the increasing needs of modern high-performance networks.

Expanding Fiber Optic Infrastructure to Propel Market Growth

Governments and commercial companies around the world are investing heavily in expanding fiber optic infrastructure, with a focus on providing high-speed internet access to underserved areas. These investments attempt to bridge the digital gap, recognizing the crucial role of digital connectivity in economic and social growth. Furthermore, improving existing infrastructure is a need to ensure that it can meet the increasing demands of future technological breakthroughs. This concentrated effort demonstrates a commitment to expanding access to high-speed internet and bolstering the backbone of digital communication networks in order to fulfill society's shifting needs and support long-term global prosperity.

Market Dynamics of the Fiber Inspection and Cleaning

High Cost of Equipment to Restrict Market Growth

The initial cost of procuring fiber inspection and cleaning equipment might be prohibitively expensive for businesses and organizations. This is especially true for specialized instruments and systems designed for fiber optic network maintenance. The large initial expenditure may dissuade some organizations from using these critical technologies, compromising their capacity to ensure optimal network performance. However, it is critical to understand that, despite the initial expenses, the long-term benefits, such as eliminating signal loss, decreasing downtime, and increasing the lifespan of fiber connections, frequently surpass the initial financial hurdles. As the significance of dependable data transmission develops, these technologies become indispensable, underscoring the importance of overcoming the initial financial barrier.

Impact of COVID-19 on the Fiber Inspection and Cleaning Market

The COVID-19 pandemic had a significant influence on the fiber inspection and cleaning business, causing supply chain interruptions and operational difficulties. Due to construction and infrastructure project lockdowns, demand for fiber optic inspection and cleaning solutions experienced a temporary delay. However, greater reliance on internet access during remote work, as well as the resumption of essential projects following lockdowns, aided the market's revival. The fiber inspection and cleaning market displayed resilience as businesses adapted to the new normal, aligning with the growing emphasis on dependable and efficient data transmission in the post-pandemic world. Introduction of the Fiber Inspection And Cleaning Market

The fiber inspection and cleaning market covers the important demand for fiber optic network performance maintenance. With the increased deployment of high-speed internet, telecommunications, and data centers, it is critical to ensure the cleanliness and integrity of fiber connections. This market includes innovative tools and equipment used to examine and clean fiber optic connectors, avoid signal loss, and im...

Abstract

Because of the importance of the household sector and due to it's large contribution to energy consumption in the Palestinian Territory, PCBS decided to conduct a special household energy survey to cover energy indicators in the household sector. To achieve this, a questionnaire was attached to the Labor Force Survey.

This survey aimed to provide data on energy consumption in the household sector and to provide data on energy consumption behavior in the society by type of energy.

This report presents data on various energy households indicators in the Palestinian Territory, and presents statistical data on electricity and other fuel consumption for the household sector, using type of fuel by different activities (cooking, Baking, conditioning, lighting, and water Heating).

Geographic coverage

Palestine.

Analysis unit

Households

Universe

The target population was all Palestinian households living in the Palestine.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The sampling frame consists of all the enumeration areas enumerated in 2007: each enumeration area consists of buildings and housing units with an average of around 124 households. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sample size The estimated sample size is 3,184 households.

Sampling Design: The sample of this survey is a part of the main sample of the Labor Force Survey (LFS), which is implemented quarterly (distributed over 13 weeks) by PCBS since 1995. This survey was attached to the LFS in the third quarter of 2013 and the sample comprised six weeks, from the eighth week to the thirteen week of the third round of the Labor Force Survey of 2013. The sample is two-stage stratified cluster sample:

First stage: selection of a stratified systematic random sample of 206 enumeration areas for the semi-round.

Second stage: selection of a random area sample of an average of 16 households from each enumeration area selected in the first stage.

Sample strata The population was divided by: 1. Governorate (16 governorates) 2. Type of locality (urban, rural, refugee camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The design of the questionnaire for the Household Energy Survey was based on the experiences of similar countries as well as on international standards and recommendations for the most important indicators, taking into account the special situation of the Palestinian Territory.

Cleaning operations

The data processing stage consisted of the following operations: Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.

Data entry: The household energy survey questionnaire was programmed onto handheld devices and data were entered directly using these devices in the West Bank. With regard to Jerusalem J1 and the Gaza Strip, data were entered into the computer in the offices in Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: · To prevent the duplication of questionnaires during data entry. · To apply checks on the integrity and consistency of entered data. · To handle errors in a user friendly manner. · The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

During fieldwork 3,184 families were visited in the Palestinian Territory, There is 2,692 complete questioner. , this percent was about 85%.

Sampling error estimates

Sampling Errors Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are anticipated in comparison with the real values obtained through censuses. The variance was calculated for the most important indicators: the variance table is attached with the final report. There is no problem in the dissemination of results at national and regional level (North, Middle, South of West Bank, Gaza Strip) and by locality. However, the indicator of averages of household consumption for certain fuels by region show a high variance.

Non Sampling Errors The implementation of the survey encountered non-response where the household was not present at home during the field work visit and where the housing unit was vacant: these made up a high percentage of the non-response cases. The total non-response rate was 10.8%, which is very low when compared to the household surveys conducted by PCBS. The refusal rate was 3.3%, which is very low compared to the household surveys conducted by PCBS and may be attributed to the short and clear questionnaire.

The survey sample consisted of around 3,184 households, of which 2,692 households completed the interview: 1,757 households from the West Bank and 935 households in the Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the West Bank was 86.8 % while in the Gaza Strip it was 94.3%.

Non-Response Cases

No. of cases non-response cases
2,692 Household completed 35 Household traveling 17 Unit does not exist 111 No one at home
102 Refused to cooperate
152 Vacant housing unit 5 No available information
70 Other
3,184 Total sample size

Response and non-response formulas:

Percentage of over coverage errors = Total cases of over coverage x 100% Number of cases in original sample = 5.3%

Non response rate = Total cases of non response x 100% Net Sample size = 10.8%

Net sample = Original sample - cases of over coverage Response rate = 100% - non-response rate = 89.2%

Treatment of non-response cases using weight adjustment

Where

the primary weight before adjustment for the household i g: adjustment group by ( governorate, locality type ). fg: weight adjustment factor for the group g. : Total weights in group g
cases : Total weights of over coverage : Total weights of response cases

We calculate fg for each group ,and final we obtain the final household weight () by using the following formula:

Comparability The data of the survey are comparable geographically and over time by comparing data from different geographical areas to data of previous surveys and the 2007 census.

Data quality assurance procedures Several procedures were undertaken to ensure appropriate quality control in the survey. Field workers were trained on the main skills prior to data collection, field visits were conducted to field workers to ensure the integrity of data collection, editing of questionnaires took place prior to data entry and a data entry application was used that prevents errors during the data entry process, then the data were reviewed. This was done to ensure that data were error free, while cleaning and inspection of anomalous values were carried out to ensure harmony between the different questions on the questionnaire.

Technical notes The following are important technical notes on the indicators presented in the results of the survey: · Some households were not present in their houses and could not be seen by interviewers. · Some households were not accurate in answering the questions in the questionnaire.
· Some errors occurred due to the way the questions were asked by interviewers. · Misunderstanding of the questions by the respondents. · Answering questions related to consumption based on estimations. · In all calculations related to gasoline, the average of all available types of gasoline was used. · In this survey, data were collected about the consumption of olive cake and coal in households, but due to lack of relevant data and fairly high variance, the data were grouped with others in the statistical tables. · The increase in consumption of electricity and the decrease in the consumption of the other types of fuel in the Gaza Strip reflected the Israeli siege imposed on the territory.

Data appraisal

The data of the survey is comparable geographically and over time by comparing the data between different geographical areas to data of previous surveys.

Layer contains sites managed under the Site Cleanup Program and is intended for use and viewing in the Site Cleanup Program GIS Story. The DWQ at the State Water Board developed this GIS Story of the Site Cleanup Program to inform the public of its mission and duties. The story intends to depict the importance of the program, describe the program's main roles and responsibilities, and provide input on the current and potential future challenges of the Site Cleanup Program. For more information on the Water Board's Site Cleanup Program visit Site Cleanup Program (SCP) | California State Water Resources Control Board.