According to the monitoring data from the Embassy of the United States, there was on average 39 micrograms of PM2.5 particles per cubic meter to be found in the air in Beijing during 2023. The air quality has improved considerably since 2013.

Reasons for air pollution in Beijing

China’s capital city Beijing is one of the most populous cities in China with over 20 million inhabitants. Over the past 20 years, Beijing’s GDP has increased tenfold. With the significant growth of vehicles and energy consumption in the country, Beijing’s air quality is under great pressure from the economic development. In the past, the city had a high level of coal consumption. Especially in winter, in which coal consumption increased due to heating, the air quality could get extremely bad on the days without wind. In spring, the wind from the north would bring sand from Mongolian deserts, resulting in severe sandstorms in Beijing. The bad air quality also affected the air visibility and threatened people’s health. On days with very bad air quality, people wearing masks for protection can be seen on the streets in the city.

Methods to improve air quality in Beijing

Over the past years, the government has implemented various methods to improve the air quality in Northern China. Sandstorms, which were quite common 15 years ago, are now rarely seen in Beijing’s spring thanks to afforestation projects on China’s northern borders. The license-plate lottery system was introduced in Beijing to restrict the growth of private vehicles. Large trucks were not allowed to enter certain areas in Beijing. Above all, the coal consumption in Beijing has been restricted by shutting down industrial sites and improving heating systems. Beijing’s efforts to improve air quality has also been highly praised by the UN as a successful model for other cities. However, there is also criticism pointing out that the improvement of Beijing’s air quality is based on the sacrifice of surrounding provinces (including Hebei), as many factories were moved from Beijing to other regions. Besides air pollution, there are other environmental problems like water pollution that China is facing. The industrial transformation is the key to China’s environmental improvement.

As of August 2025, the average monthly air quality index in Beijing stood at **, which is within the ********** range, making it one of the months with better air quality compared to the rest of the year. Air Pollution in Beijing For years, Beijing has earned a notorious reputation for having air quality detrimental to health. For the same survey period, Beijing has the worst average air quality among other Chinese cities such as Chengdu, Shanghai, Guangzhou and Shenyang. The pollution caused by PM2.5 has been worsening since 2008 as the manufacturing industry around the capital grew and the demand for energy and heat increased. However, since the government began to tackle the issue, pollution levels in Beijing have improved significantly. Causes of air pollution in China and tackling the root cause Much of the air pollution in China is associated with the burning of coal, especially in the industrial sector, and transportation. With the emergence of the public health concern, the Chinese government also introduced plans to ease the air pollution, including setting targets for fine particulate matter, completion of construction and renovation of pollution control facilities, introducing vehicle control, and electrifying the fleet of public buses. In addition, the popularity and prevalence of electric vehicles also contributed to the reduced exhaust fume-based pollution.

This data set includes hourly air pollutants data from 12 nationally-controlled air-quality monitoring sites. The air-quality data are from the Beijing Municipal Environmental Monitoring Center. The meteorological data in each air-quality site are matched with the nearest weather station from the China Meteorological Administration. The time period is from March 1st, 2013 to February 28th, 2017. Missing data are denoted as NA.

China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei Region data was reported at 44.000 mcg/Cub m in May 2018. This records a decrease from the previous number of 52.000 mcg/Cub m for Apr 2018. China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei Region data is updated monthly, averaging 68.000 mcg/Cub m from Mar 2013 (Median) to May 2018, with 61 observations. The data reached an all-time high of 151.000 mcg/Cub m in Feb 2014 and a record low of 37.000 mcg/Cub m in Aug 2016. China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei Region data remains active status in CEIC and is reported by China National Environmental Monitoring Centre. The data is categorized under China Premium Database’s Environmental Protection – Table CN.EPJ: Air Quality: PM2.5 Concentration: Region.

This dataset is part of the Monash, UEA & UCR time series regression repository. http://tseregression.org/

The goal of this dataset is to predict PM2.5 air quality in the city of Beijing. This dataset contains 17532 time series with 9 dimensions. This includes hourly air pollutants measurments (SO2, NO2, CO and O3), temperature, pressure, dew point, rainfall and windspeed measurments from 12 nationally controlled air quality monitoring sites. The air-quality data are from the Beijing Municipal Environmental Monitoring Center. The meteorological data in each air-quality site are matched with the nearest weather station from the China Meteorological Administration. The time period is from March 1st, 2013 to February 28th, 2017.

Please refer to https://archive.ics.uci.edu/ml/datasets/Beijing+Multi-Site+Air-Quality+Data for more details

Relevant Papers
Zhang, S., Guo, B., Dong, A., He, J., Xu, Z. and Chen, S.X. (2017) Cautionary Tales on Air-Quality Improvement in Beijing. Proceedings of the Royal Society A, Volume 473, No. 2205, Pages 20170457

Citation Request
Zhang, S., Guo, B., Dong, A., He, J., Xu, Z. and Chen, S.X. (2017) Cautionary Tales on Air-Quality Improvement in Beijing. Proceedings of the Royal Society A, Volume 473, No. 2205, Pages 20170457

This dataset contains synthetic but realistic air pollution data from five major cities in China: Beijing, Shanghai, Guangzhou, Chengdu, and Shenzhen. It spans from 2015 to 2025, providing valuable information on air quality, meteorological conditions, and pollution levels. The dataset is structured with 3,000 rows and 24 columns, covering various air pollutants, weather conditions, and geographical details.

The dataset is designed for data analysis, machine learning models, and air quality forecasting applications.

Dataset

This dataset was created by Manojkumar D

Released under MIT

Contents

China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei and Vicinity (55 City) data was reported at 36.000 mcg/Cub m in Sep 2018. This records an increase from the previous number of 35.000 mcg/Cub m for Aug 2018. China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei and Vicinity (55 City) data is updated monthly, averaging 38.000 mcg/Cub m from Jun 2018 (Median) to Sep 2018, with 4 observations. The data reached an all-time high of 42.000 mcg/Cub m in Jun 2018 and a record low of 35.000 mcg/Cub m in Aug 2018. China Air Quality: PM2.5 Concentration: Monthly Average: Beijing-Tianjin-Hebei and Vicinity (55 City) data remains active status in CEIC and is reported by China National Environmental Monitoring Centre. The data is categorized under China Premium Database’s Environmental Protection – Table CN.EPJ: Air Quality: PM2.5 Concentration: Region.

In this study, Beijing, the capital of China, is selected as the study area. Hourly mean concentrations of six regulatory air pollutants including O3 (μg/m3), SO2 (μg/m3), NO2 (μg/m3), PM2.5 (μg/m3), PM10 (μg/m3), and CO (mg/m3) were collected from 35 air quality monitoring stations labeled by 1 to 35 from 01/01/2017 to 05/30/2018. The data was provided by the Ministry of Environmental Protection (MEP) of China. Hourly averaged meteorological data in the same period were first accessed from The National Oceanic and Atmospheric Administration (NOAA), then processed by the Weather Research and Forecasting (WRF) model to produce grid meteorological data (21×31 points) with a grid spacing of 5 km. Meteorological parameters including temperature, air pressure, relative humidity, wind speed, and wind direction are selected as the main meteorological features due to their close relationships with the change of ozone concentrations.

In 2024, the average concentration of PM10 decreased by around *** percent in Jing-Jin-Ji Metropolitan Area around Beijing, China. The air quality of China has been gradually improving after years of effort put into anti-air pollution measures.

Although studies have increasingly linked air pollution to specific health outcomes, less well understood is how public perceptions of air quality respond to changing pollutant levels. The growing availability of air pollution measurements and the proliferation of social media provide an opportunity to gauge public discussion of air quality conditions. In this paper, we consider particulate matter (PM) measurements from four Chinese megacities (Beijing, Shanghai, Guangzhou, and Chengdu) together with 112 million posts on Weibo (a popular Chinese microblogging system) from corresponding days in 2011–2013 to identify terms whose frequency was most correlated with PM levels. These correlations are used to construct an Air Discussion Index (ADI) for estimating daily PM based on the content of Weibo posts. In Beijing, the Chinese city with the most PM as measured by U.S. Embassy monitor stations, we found a strong correlation (R = 0.88) between the ADI and measured PM. In other Chinese cities with lower pollution levels, the correlation was weaker. Nonetheless, our results show that social media may be a useful proxy measurement for pollution, particularly when traditional measurement stations are unavailable, censored or misreported.

Air Quality Forecast: Contaminant Concentration: Ozone: China: Beijing data was reported at 43.467 mcg/Cub m in 22 May 2025. This records a decrease from the previous number of 47.887 mcg/Cub m for 21 May 2025. Air Quality Forecast: Contaminant Concentration: Ozone: China: Beijing data is updated daily, averaging 27.147 mcg/Cub m from Oct 2019 (Median) to 22 May 2025, with 2038 observations. The data reached an all-time high of 147.614 mcg/Cub m in 24 Jul 2022 and a record low of 0.285 mcg/Cub m in 09 Dec 2021. Air Quality Forecast: Contaminant Concentration: Ozone: China: Beijing data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s China – Table CAMS.AQF: Air Quality Forecast: Contaminant Concentration: Ozone: by Cities. [COVID-19-IMPACT]

Information of Weibo posts and air quality condition in four mega cities of China for this study.

Air Quality: PM2.5 Concentration: Annually Average: Beijing data was reported at 33.000 mcg/Cub m in 2021. This records a decrease from the previous number of 38.000 mcg/Cub m for 2020. Air Quality: PM2.5 Concentration: Annually Average: Beijing data is updated yearly, averaging 58.000 mcg/Cub m from Dec 2013 (Median) to 2021, with 9 observations. The data reached an all-time high of 89.500 mcg/Cub m in 2013 and a record low of 33.000 mcg/Cub m in 2021. Air Quality: PM2.5 Concentration: Annually Average: 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 Environmental Protection – Table CN.EPK: Air Quality: PM2.5 Concentration: Prefecture Level City.

Dataset

This dataset was created by Giridhar Vasu

Released under CC0: Public Domain

Contents

In 2023, the average concentration of PM 2.5 was around ** micrograms per cubic meter in Beijing, China. The air quality of China has been gradually improving after years of effort put into anti-air pollution measures.

The air quality in Beijing, especially its PM2.5 level, has become of increasing public concern because of its importance and sensitivity related to health risks. A set of monitored PM2.5 data from 31 stations, released for the first time by the Beijing Environmental Protection Bureau, covering 37 days during autumn 2012, was processed using spatial interpolation and overlay analysis. Following analyses of these data, a distribution map of cumulative exceedance days of PM2.5 and a temporal variation map of PM2.5 for Beijing have been drawn. Computational and analytical results show periodic and directional trends of PM2.5 spreading and congregating in space, which reveals the regulation of PM2.5 overexposure on a discontinuous medium-term scale. With regard to the cumulative effect of PM2.5 on the human body, the harm from lower intensity overexposure in the medium term, and higher overexposure in the short term, are both obvious. Therefore, data of population distribution were integrated into the aforementioned PM2.5 spatial spectrum map. A spatial statistical analysis revealed the patterns of PM2.5 gross exposure and exposure probability of residents in the Beijing urban area. The methods and conclusions of this research reveal relationships between long-term overexposure to PM2.5 and people living in high-exposure areas of Beijing, during the autumn of 2012.

Experimental results of different methods in Beijing air quality dataset.

1) Data Introduction • The Industrial-Residential Air Quality Classification Dataset is based on daily air pollution data measured in six cities, including Moscow, Delhi, Beijing, Zurich, Vancouver, and Stockholm, in 2024 and is designed to analyze air quality differences and the impact of urban environments by dividing each city into industrial or residential areas.

2) Data Utilization (1) Industrial-Residential Air Quality Classification Dataset has characteristics that: • This dataset consists of daily measurements for each city, including city name, date of measurement, concentration of six types of air pollutants (standard unit: ppm CO₂, µg/m ³) and city type (industrial/residential) labels for all samples. • It is designed to compare the air quality characteristics of industrial districts (three cities) and residential districts (three cities), and the unit of measurement and label criteria are clearly standardized. (2) Industrial-Residential Air Quality Classification Dataset can be used to: • Air Quality Based Urban Type Classification Model Development: Using pollutant concentrations as input variables, it can be used for machine learning classifiers to predict whether the city is an industrial or residential district. • Major pollutant correlation analysis: It can be used for variable importance analysis and correlation studies on how important certain pollutants, such as PM2.5, NO₂, are to distinguish industrial and residential districts. • Comparison of industrial/residential air quality trends: It can be used as a basis for urban planning and environmental policy establishment by comparing and analyzing air quality change patterns throughout the year by city type. • Environmental and Policy Studies: By analyzing pollutant concentrations and their association with city type, city-specific environmental regulations, and urban planning policies, it can be applied to urban environment improvement and policy effectiveness assessment.

Dataset

This dataset was created by David Havera

Released under CC0: Public Domain

Contents