In 2023, Shanghai was the city with the largest GDP in China, reaching a value added of approximately *** trillion yuan. The four Chinese first-tier cites Beijing, Shanghai, Shenzhen, and Guangzhou had by far the strongest economic performance. Development of Chinese cities Rapid urbanization and economic growth have reshaped all Chinese cities since the economic opening up of China. While the first-tier cities have overall benefitted most from this development, the last two decades have seen many second-tier cities catching up. For many years already, growth rates in Qingdao, Hangzhou, Changsha, and Zhengzhou have been higher than in Shanghai or Beijing.This development was driven by lower costs in smaller cities, a specialization of their economies, and political measures to support inland cities and ease the pressure on the largest municipalities. Today, per capita GDP in cities such as Suzhou, Nanjing, and Shenzhen is already higher than in Beijing or Shanghai. Future perspectives Competition between cities will further change China’s urban landscape in the future. Medium-sized cities that can provide an attractive economic environment have the potential to grow their economy at a faster pace, attract immigration, and further increase their relative importance. Cities that are losing their competitive edge, however, like Shenyang, Dalian, and other cities in the northeastern rustbelt, are increasingly confronted by economic stagnation and demographic decline.

Per capita gross domestic product (GDP) of cities in China varies tremendously, mainly depending on the location of the city. Cities with the highest per capita GDP are mainly to be found in coastal provinces in East China and in South China, like Guangdong province. The poorest cities are located in the still less developed western parts of China, like Gansu province, or in the Chinese rust belt in Northeastern China, like Heilongjiang province.

This dataset collects the price information of second-hand houses in the top 10 cities in China in 2021(GDP). The website for obtaining information is Anjuke, and the amount of data on each city is about 3,000.

Language: Parts of the table in this dataset are in Chinese, but these colunms in Chinese have a certain range of values which could be transformed into index. There for, I choose to remain the origin language on these colunms, making it more likely to keep the original information as possible.

According to a report on Chinese cities from 2024 that provided a ranking of their economic clout, Beijing, Shanghai, and Hong Kong shared first place with a total composite score of ***. The overall city ranking, which consisted of ten subsets, was headed by China's capital Beijing.

GDP: Shanghai data was reported at 5,392.671 RMB bn in 2024. This records an increase from the previous number of 5,140.447 RMB bn for 2023. GDP: Shanghai data is updated yearly, averaging 51.814 RMB bn from Dec 1949 (Median) to 2024, with 76 observations. The data reached an all-time high of 5,392.671 RMB bn in 2024 and a record low of 2.028 RMB bn in 1949. GDP: Shanghai data remains active status in CEIC and is reported by Shanghai Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City.

In 2024, the annual per capita gross domestic product (GDP) in different provinces, municipalities, and autonomous regions in China varied from approximately 228,200 yuan in Beijing municipality to roughly 52,800 yuan in Gansu province. The average national per capita GDP crossed the threshold of 10,000 U.S. dollars in 2019 and reached around 95,700 yuan in 2024. Regional economic differences in China The level of economic development varies considerably in different parts of China. Four major geographic and economic regions can be discerned in the country: The economically advanced coastal regions in the east, less developed regions in Northeast and Central China, and the developing regions in the west. This division has deep historical roots reflecting the geography of each region and their political past and present. Furthermore, regional economic development closely correlates with regional urbanization rates, which closely resembles the borders of the four main economic regions. Private income in different parts of China Breaking the average income figures further down by province, municipality, or autonomous region reveals that the average disposable income in Shanghai or Beijing is on average more than three times higher than in Tibet or Gansu province. In rural areas, average disposable income is often only between one third and one half of that in urban areas of the same region. Accordingly, consumer expenditure per capita in urban areas reaches the highest levels in Shanghai, Beijing, and the coastal regions of China.

GDP: Guangdong: Shenzhen data was reported at 3,680.187 RMB bn in 2024. This records an increase from the previous number of 3,490.327 RMB bn for 2023. GDP: Guangdong: Shenzhen data is updated yearly, averaging 277.009 RMB bn from Dec 1979 (Median) to 2024, with 46 observations. The data reached an all-time high of 3,680.187 RMB bn in 2024 and a record low of 0.196 RMB bn in 1979. GDP: Guangdong: Shenzhen data remains active status in CEIC and is reported by Shenzhen Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City.

GDP: Year to Date: Primary Industry: Guangdong: Guangzhou data was reported at 3.760 RMB bn in Mar 2025. This records a decrease from the previous number of 33.447 RMB bn for Dec 2024. GDP: Year to Date: Primary Industry: Guangdong: Guangzhou data is updated quarterly, averaging 13.022 RMB bn from Dec 2000 (Median) to Mar 2025, with 63 observations. The data reached an all-time high of 33.447 RMB bn in Dec 2024 and a record low of 3.760 RMB bn in Mar 2025. GDP: Year to Date: Primary Industry: Guangdong: Guangzhou data remains active status in CEIC and is reported by Guangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Primary Industry: Quarterly.

In 2024, the gross domestic product (GDP) of Shanghai municipality in China amounted to approximately **** trillion yuan. Shanghai is the most populous city in China and has the largest GDP of all Chinese cities. It is located in Eastern China on the southern estuary at the mouth of the Yangtze river. Development of GDP in Shanghai The GDP of Shanghai has previously grown at a high pace, but economic development has gradually lost momentum over the years. GDP growth in Shanghai, which developed very close to national figures in recent years, ranged at *** percent in 2024. From a sectoral point of view, the tertiary sector of the economy displayed the highest growth rates in most of the past years and services already account for more than ** percent of the value added to the GDP. In contrast, the share of the industrial sector, which had once been of great importance to Shanghai, has been shrinking in most of the years. Branches in the service sector of the economy that experienced the fastest development were financial intermediation and information industries. Per capita GDP in Shanghai Set in relation to the population size of the city, the economic success of its inhabitants becomes apparent. Per capita GDP of Shanghai citizens exceeded ****** U.S. dollars on average for the first time in 2019, which is in the global middle field and well above the average in East Asia. However, when comparing it to other cities or regions, it has to be taken into account that the administrative area of Shanghai municipality is quite large and includes distant suburbs as well as villages on agrarian land. For this reason, Shanghai’s per capita GDP is quite high and only second to Beijing when it is compared on a provincial level in mainland China. However, when compared on a city level, with other Chinese cities often having smaller administrative areas not including distant suburbs, Shanghai’s per capita GDP ranks only within the leading 10 cities.

GDP: TI: Education: Sichuan: Chengdu data was reported at 32.459 RMB bn in 2017. This records an increase from the previous number of 29.590 RMB bn for 2016. GDP: TI: Education: Sichuan: Chengdu data is updated yearly, averaging 22.393 RMB bn from Dec 2000 (Median) to 2017, with 10 observations. The data reached an all-time high of 32.459 RMB bn in 2017 and a record low of 3.833 RMB bn in 2000. GDP: TI: Education: Sichuan: Chengdu data remains active status in CEIC and is reported by Chengdu Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: TI: Education.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Culture, Sport and Entertainment: Guangdong: Foshan data was reported at 134.380 Prev Year=100 in 2017. This records an increase from the previous number of 118.100 Prev Year=100 for 2016. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Culture, Sport and Entertainment: Guangdong: Foshan data is updated yearly, averaging 118.300 Prev Year=100 from Dec 2005 (Median) to 2017, with 10 observations. The data reached an all-time high of 134.380 Prev Year=100 in 2017 and a record low of 85.888 Prev Year=100 in 2012. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Culture, Sport and Entertainment: Guangdong: Foshan data remains active status in CEIC and is reported by Foshan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Culture, Sport and Entertainment.

In 2021, around **** million people were estimated to be living in the urban area of Shanghai. Shanghai was the largest city in China in 2021, followed by Beijing, with around **** million inhabitants. The rise of the new first-tier cities The past decades have seen widespread and rapid urbanization and demographic transition in China. While the four first-tier megacities, namely Beijing, Shanghai, Guangzhou, and Shenzhen, are still highly attractive to people and companies due to their strong ability to synergize the competitive economic and social resources, some lower-tier cities are already facing declining populations, especially those in the northeastern region. Below the original four first-tier cities, 15 quickly developing cities are sharing the cake of the moving population with improving business vitality and GDP growth potential. These new first-tier cities are either municipalities directly under the central government, such as Chongqing and Tianjin, or regional central cities and provincial capitals, like Chengdu and Wuhan, or open coastal cities in the economically developed eastern regions. From urbanization to metropolitanization As more and more Chinese people migrate to large cities for better opportunities and quality of life, the ongoing urbanization has further evolved into metropolitanization. Among those metropolitans, Shenzhen's population exceeded **** million in 2020, a nearly ** percent increase from a decade ago, compared to eight percent in the already densely populated Shanghai. However, with people rushing into the big-four cities, the cost of housing, and other living standards, are soaring. As of 2020, the average sales price for residential real estate in Shenzhen exceeded ****** yuan per square meter. As a result, the fast-growing and more cost-effective new first-tier cities would be more appealing in the coming years. Furthermore, Shanghai and Beijing have set plans to control the size of their population to ** and ** million, respectively, before 2035.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Transport, Storage and Post: Fujian: Quanzhou data was reported at 112.400 Prev Year=100 in 2021. This records an increase from the previous number of 107.700 Prev Year=100 for 2018. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Transport, Storage and Post: Fujian: Quanzhou data is updated yearly, averaging 108.250 Prev Year=100 from Dec 2010 (Median) to 2021, with 10 observations. The data reached an all-time high of 112.400 Prev Year=100 in 2021 and a record low of 94.300 Prev Year=100 in 2016. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Transport, Storage and Post: Fujian: Quanzhou data remains active status in CEIC and is reported by Quanzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Transport, Storage and Post.

It is widely believed that political hierarchy correlates with regional development. This paper investigates the impact of the political hierarchies of cities in China from different perspectives. First, we examine the economic development differences between prefectural cities and municipalities. Furthermore, this paper draws upon a quasi-experiment to analyze the impact of upgrading Chongqing to a municipality in 1997 using the synthetic control method. The city-upgrading policy significantly increased Chongqing's GDP in the following four years. Finally, we find that the policy increased GDP in treated cities located within 1200 kilometers of Chongqing by about 10%-13% relative to the control cities.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Real Estate: Fujian: Quanzhou data was reported at 105.500 Prev Year=100 in 2021. This records a decrease from the previous number of 107.000 Prev Year=100 for 2018. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Real Estate: Fujian: Quanzhou data is updated yearly, averaging 107.750 Prev Year=100 from Dec 2010 (Median) to 2021, with 10 observations. The data reached an all-time high of 116.700 Prev Year=100 in 2013 and a record low of 96.300 Prev Year=100 in 2014. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Real Estate: Fujian: Quanzhou data remains active status in CEIC and is reported by Quanzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Real Estate.

Summary

This metadata record provides details of the data supporting the claims of the related manuscript: “Water scarcity will constrain the formation of a world-class megalopolis in North China”.

The data consist of 15 Excel .xlsx format data files.

The related study investigated the water challenge the water-scarce Beijing-Tianjin-Hebei (BTH) region faces under China’s goal of developing it into a world-class megalopolis, and the effects of the main water conservation measures in the region towards the goal.

Data access

The data generated and analysed during the related study are publicly available as part of this data record. The 15 Excel files are listed below, along with the names of the figures and supplementary tables from the manuscript that each file supports in square brackets.1-Economic growth &Water use: This table provides the data of GDP and water use in the BTH region and existing world-class megalopolises (2017). The data sources include United States Geological Survey, The Great Lakes Regional Water Use Database, Statistics of Tokyo, Eurostat, and National Bureau of Statistics of China. [Figure 1]

2-The BTH economic and water resource conditions: This table provides the city-level data of the economic and water resource conditions in the BTH region (2017). The data sources include China Statistical Yearbook, Hebei Economic Yearbook, and Water Resources Bulletin of Beijing, Tianjin, and Hebei. [Figure 2 and Supplementary Table 4]

3-Water gaps: This table provides the data of water gaps for the BTH region to achieve the two benchmarking goals. The data in the column of ‘Minimum water requirement’ are from model simulation and the data in the column of ‘Average water resources’ are calculated based on official data from China Statistical Yearbook. Water gaps are obtained by subtracting the latter from the former. [Figure 3]

4-GDP comparison: This table provides the GDP data of the BTH region and the existing world-class megalopolises. BTH region’s maximum GDP data are from model simulation and the rest of the GDP data are officially released data. The data sources include Bureau of Economic Analysis, Eurostat, Tokyo Statistical Yearbook, and China Statistical Yearbook. [Figure 4]

5-Measure effects: This table provides the data of the effects of the applications of water conservation measures. The data in the column of ‘Minimum water requirement’ are from model simulation and the data in the column of ‘The BTH annual average water resources’ are calculated based on official data from China Statistical Yearbook. ‘Water saved by the measures’ are obtained by subtracting the ‘minimum water requirement’ of each measure from the ‘minimum water requirement’ of ‘No conservation measure applied’. [Figure 5]

6-Water gaps_four-city-excluded: This table provides the data of the water gaps for the four-city-excluded BTH region to achieve the two benchmarking goals. The data are from model simulation, in which four cities (Handan, Xingtai, Hengshui and Cangzhou) are excluded from the BTH region. [Figure 6]

7- Economic size : This table provides the GDP data of the BTH region and the six world-class megalopolises (2017). The data sources include Bureau of Economic Analysis, Eurostat, Statistics of Tokyo, National Bureau of Statistics of China. The exchange rate between USD and CNY is based on the averaged central parity rate of year 2017 released by the People's Bank of China. [Supplementary Table 1]

8- Industrial structure : This table provides the data of the industrial structure of the BTH cities (2017). The data are provided by Hebei Provincial Bureau of Statistics and National Bureau of Statistics of China. [Supplementary Table 2]

9- Trade data : This table provides the data of the total trade of the BTH cities with their trade partners. The data are calculated based on inter-city input-output table of the BTH region (2012). Total trade value is the summation of the bilateral trade amount between the BTH cities and their trade partners. The exchange rate between USD and CNY is based on the averaged central parity rate of year 2012 released by the People's Bank of China. [Supplementary Table 3]

10- Indicators for benchmarks: This table provides the data of representing indicators as criteria for the BTH region's goal of being a world-class megalopolis in model settings. The data are obtained from National Bureau of Statistics of China, Shanghai Bureau of Statistics, Zhejiang provincial Bureau of Statistics, Jiangsu provincial Bureau of Statistics, Bureau of Economic Analysis, and Great Lakes Maritime Research Institute. [Supplementary Table 5]

11- Objective of water use efficiency: This table provides the data of water control objective for improving water use efficiency in the BTH region. The Data Sources include: 1) The People’s Government of Beijing Municipality. Beijing Water Development Plan for 'the 13th Five-Year Plan' Period, (2016-7-8). 2) Tianjin Municipal People’s Government. Tianjin Action Plan for Dual Control of Total Water Consumption and Intensity for ‘the 13th Five-Year Plan' Period, (2017-3-30). 3) The People’s Government of Hebei Province. Hebei Implementation Plan for Dual Control of Total Water Consumption and Intensity 2016-2020, (2017-3-7). [Supplementary Table 6]

12-SNWTP water use: This table provides the data of the SNWTP water use in the water intake cities of the BTH region (2018). The data are provided by Water Transfer Management Office in Department of Water Resources of Hebei Province. [Supplementary Table 7]

13- Macroeconomic parameter comparison_provincial level: This table provides the key macroeconomic parameters at provincial level. The data sources include Beijing Municipal Bureau of Statistics, Tianjin Municipal Bureau of Statistics and Hebei Provincial Bureau of Statistics. [Supplementary Table 8]

14- Macroeconomic parameter comparison_city level: This table provides the key macroeconomic parameters at city level. The data are provided by National Bureau of Statistics of China and Hebei Provincial Bureau of Statistics. [Supplementary Table 9]15- Water parameter comparison_city level: This table provides the key water use related parameters at city level. The data are provided by Beijing Water Authority, Tianjin Water Authority, and Department of Water Resources of Hebei Province. [Supplementary Table 10]

The per capita GDP contribution of Shanghai amounted to around ******* yuan in 2024, up from ******* yuan in the previous year. Shanghai is one of the largest cities in China. In terms of GDP, it was also the Chinese city with the largest GDP contribution, followed by Beijing and Shenzhen. Shanghai's economic development Shanghai’s GDP growth rate ranged at *** percent in 2024, the same as Chinese national GDP growth. As the leading city in the Yangtze River Delta Economic Zone, Shanghai is one of the most active cities for business and trade in China. While the share of the industrial sector in Shanghai’s GDP continues to shrink, the city’s economy is becoming increasingly reliant on the service sector. In 2013, the first free-trade zone in Mainland China was launched in Shanghai, making Shanghai play an essential role in China’s economic reforms. A friendlier investment environment, less tax burdens and a more open financial market for foreign companies were expected to be promoted there. Living in Shanghai Shanghai became world famous when it was recognized by the Europeans in the 19th century for its economic potential as an important harbor city. Today, it is still one of the most open and active cities in China. Migration from across China and other countries makes Shanghai a melting pot of different cultures, which can also be found in its diverse catering industry. In terms of housing prices, it’s one of the most expensive cities in China. Still, the colorful life and plentiful opportunities are attracting numerous young people to come to the city for study and work.

A number of studies have reported the contents of PAHs (polycyclic aromatic hydrocarbons) in PM (particulate matter) in cities. These studies were published from 2000 to 2019 and include analyses of PAH contamination in response to rapid socioeconomic development in China, considering population increases, growing energy demand, and increases in industrial production. Publications in the scientific literature were selected following the eligibility criteria described below. Original studies published in English databases (e.g., Elsevier, Springer, and Wiley) and excellent works published in Chinese databases (e.g., CNKI, CQVIP, and Wanfang Data) were included. We searched for papers and books with the keywords “polycyclic aromatic hydrocarbon in the particulate matter†, “PAH in the particulate matter†, “polycyclic aromatic hydrocarbon in PM†, “PAH in PM†, and “City, China†. Thus, we retrieved almost all the relevant reports about PAHs in PM in Chinese cities. After removing duplicate or..., , # Ecological and health risks of polycyclic aromatic hydrocarbons in particulate matter in Chinese cities

Dataset DOI: 10.5061/dryad.c59zw3rm1

Description of the data and file structure

This datasets has tables containing the location of urban, sample date, samples sites, samples number, range and mean of PAHs, and population and GDP for each urban area.

Abbreviation Listing

PAHs: Polycyclic Aromatic Hydrocarbons

GDP: Gross domestic product

PM: Particulate matter

HI: Hazard index

ILCR: Lifetime incremental cancer risk

NC: North China

CC: Central China

SC: South China

LOD: limit of detection

TEF: toxic equivalency factor

RfC: reference content for inhalation

ERM-Q:Â Effect range median quotient

LMW-PAHs: Low-molecular-weight PAHs

MMW-PAHs: Medium-molecular-weight PAHs

HMW-PAHs: High-molecular-weight PAHs

CAN-PAHs:Â Carcinogenic PAHs

NCAN-PAHs: Noncarcinogenic PAHs

COM-PAHs: Combustion-derived PAHs

Contents

Table S1 PAH c...,

GDP: Beijing data was reported at 4,984.310 RMB bn in 2024. This records an increase from the previous number of 4,735.370 RMB bn for 2023. GDP: Beijing data is updated yearly, averaging 41.022 RMB bn from Dec 1952 (Median) to 2024, with 73 observations. The data reached an all-time high of 4,984.310 RMB bn in 2024 and a record low of 0.788 RMB bn in 1952. GDP: Beijing data remains active status in CEIC and is reported by Beijing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Education: Guangdong: Foshan data was reported at 104.005 Prev Year=100 in 2017. This records an increase from the previous number of 103.000 Prev Year=100 for 2016. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Education: Guangdong: Foshan data is updated yearly, averaging 109.427 Prev Year=100 from Dec 2005 (Median) to 2017, with 10 observations. The data reached an all-time high of 124.800 Prev Year=100 in 2010 and a record low of 103.000 Prev Year=100 in 2016. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Education: Guangdong: Foshan data remains active status in CEIC and is reported by Foshan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Education.