Long-term air pollution data with high temporal and spatial resolutions are needed to support the research of physical and chemical processes that affect the air quality, and the corresponding health ...risks. However, such datasets were not available in China until recently. For the first time, this study examines the spatial and temporal variations of PM2.5, PM10, CO, SO2, NO2, and 8h O3 in 31 capital cities in China between March 2013 and February 2014 using hourly data released by the Ministry of Environmental Protection (MEP) of China. The annual mean concentrations of PM2.5 and PM10 exceeded the Chinese Ambient Air Quality Standards (CAAQS), Grade I standards (15 and 40μg/m3 for PM2.5 and PM10, respectively) for all cities, and only Haikou, Fuzhou and Lasa met the CAAQS Grade II standards (35 and 70μg/m3 for PM2.5 and PM10, respectively). Observed PM2.5, PM10, CO and SO2 concentrations were higher in cities located in the North region than those in the West and the South-East regions. The number of non-attainment days was highest in the winter, but high pollution days were also frequently observed in the South-East region during the fall and in the West region during the spring. PM2.5 was the largest contributor to the air pollution in China based on the number of non-attainment days, followed by PM10, and O3. Strong correlation was found between different pollutants except for O3. These results suggest great impacts of coal combustion and biomass burning in the winter, long range transport of windblown dust in the spring, and secondary aerosol formation throughout the year. Current air pollution in China is caused by multiple pollutants, with great variations among different regions and different seasons. Future studies should focus on improving the understanding of the associations between air quality and meteorological conditions, variations of emissions in different regions, and transport and transformation of pollutants in both intra- and inter-regional contexts.
•Temp-spatial variations of air pollutants in 31 Chinese cities were analyzed.•Major cities in China experience severe air pollution.•Significant temp-spatial differences in criteria air pollutants were observed.•Strong correlation was found between different pollutants except for O3.•China’s pollution is caused by multi-pollutants with temp-spatial variations.
The North China Plain (NCP) and the Yangtze River Delta (YRD) in China have been experiencing severe particulate matter (PM) pollution problems associated with the rapid economic growth and the ...accelerated urbanization. In this study, hourly mass concentrations of PM2.5 and PM10 during June 1st–August 31st, 2013 were collected in 13 cities located in or adjacent to the NCP region and 20 cities located in the YRD region. The overall average PM2.5 and PM10 concentrations were 77.0 μg/m3 and 136.2 μg/m3 in the NCP region, respectively, and 42.8 μg/m3 and 74.9 μg/m3 in the YRD region, respectively. The frequencies of occurrence of concentrations exceeding the China's Ambient Air Quality Standard (AAQS) (BG3095-12) Grade I standards were 83% for PM2.5 and 93% for PM10 in the NCP region, and 51% for PM2.5 and 66% for PM10 in the YRD region. Strong temporal correlation for both PM2.5 and PM10 between cities within 250 km was frequently observed. PM2.5 was found to be negatively associated with wind speed. On the PM2.5 episode days (when the 24 h PM2.5 concentration is greater than 75 μg/m3), average PM2.5 concentrations were 2–4 times greater compared to the non-episode days. The PM2.5 to PM10 ratio increased from 0.50 (0.57) on the non-episode days to 0.64 (0.64) on the episode days in the NCP (YRD) region. No distinct weekday/weekend difference was observed for PM2.5, PM10, and other gaseous pollutants (CO, SO2, NO2, and O3) in all cities. The results presented in this paper will serve as an important basis for future regional air quality modeling and source apportionment studies.
•Summertime PM2.5 and PM10 in the NCP and YRD regions of China were analyzed.•Average PM2.5 and PM10 concentrations are 77.0 and 136.2 μg/m3 in the NCP region.•Average PM2.5 and PM10 concentrations are 42.8 and 74.9 μg/m3 in the YRD region.•Strong temporal correlation between cities within 250 km is found.•PM2.5 concentrations on episode days are 2–4 times greater than non-episode days.
Exposure to fine particulate matter (PM2.5) has become a major global health concern. Although modeling exposure to PM2.5 has been examined in China, accurate long-term assessment of PM2.5 exposure ...with high spatiotemporal resolution at the national scale is still challenging. We aimed to establish a hybrid spatiotemporal modeling framework for PM2.5 in China that incorporated extensive predictor variables (satellite, chemical transport model, geographic, and meteorological data) and advanced machine learning methods to support long-term and short-term health studies. The modeling framework included three stages: (1) filling satellite aerosol optical depth (AOD) missing values; (2) modeling 1 km × 1 km daily PM2.5 concentrations at a national scale using extensive covariates; and (3) downscaling daily PM2.5 predictions to 100-m resolution at a city scale. We achieved good model performances with spatial cross-validation (CV) R 2 of 0.92 and temporal CV R 2 of 0.85 at the air quality sites across the country. We then estimated daily PM2.5 concentrations in China from 2013 to 2019 at 1 km × 1 km grid cells. The downscaled predictions at 100 m resolution greatly improved the spatial variation of PM2.5 concentrations at the city scale. The framework and data set generated in this study could be useful to PM2.5 exposure assessment and epidemiological studies.
It is a puzzle as to why more severe haze formed during the New Year Holiday in 2020 (NYH‐20), when China was in an unprecedented state of shutdown to contain the coronavirus (COVID‐19) outbreak, ...than in 2019 (NYH‐19). We performed a comprehensive measurement and modeling analysis of the aerosol chemistry and physics at multiple sites in China (mainly in Shanghai) before, during, and after NYH‐19 and NYH‐20. Much higher secondary aerosol fraction in PM2.5 were observed during NYH‐20 (73%) than during NYH‐19 (59%). During NYH‐20, PM2.5 levels correlated significantly with the oxidation ratio of nitrogen (r2 = 0.77, p < 0.01), and aged particles from northern China were found to impede atmospheric new particle formation and growth in Shanghai. A markedly enhanced efficiency of nitrate aerosol formation was observed along the transport pathways during NYH‐20, despite the overall low atmospheric NO2 levels.
Plain Language Summary
In China, there are multiple cases (e.g., the 2008 Summer Olympics in Beijing and the 2010 World Expo in Shanghai) when combustion‐related emissions (e.g., NOx) were actively, and successfully, reduced to transiently improve air quality. During the extended Chinese Lunar New Year holiday in 2020 (between 24 January and 10 February), whole China was in an unprecedented state of shutdown, because most people were contained in their homes to reduce the spread of the novel coronavirus disease (COVID‐19). Mobility, energy demand, and industrial output remained far below their normal levels. Nevertheless, widespread haze pollution still occurred over Eastern China. To elucidate haze formation mechanisms, we performed comprehensive and continuous measurements of aerosol chemistry and physics in and out of Shanghai before, during, and after the Chinese New Year Holiday in 2019 and 2020, respectively. We argue that the synergistic effects of long‐range transport and atmospheric chemistry leading to the efficient conversion of NOx to particulate nitrate were the key of haze formation during the Chinese New Year Holiday of the COVID‐19 outbreak in Shanghai.
Key Points
Higher concentrations and distinct compositions of aerosol particles were observed during the COVID‐19 shutdown
Fast formation of secondary inorganic aerosol contributed to high aerosol mass loading
Longer‐range, regional transport facilitated and enhanced particulate nitrate formation
Excess mortality (ΔMort) in China due to exposure to ambient fine particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) was determined using an ensemble prediction of annual average PM2.5 in ...2013 by the community multiscale air quality (CMAQ) model with four emission inventories and observation data fusing. Estimated ΔMort values due to adult ischemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, and lung cancer are 0.30, 0.73, 0.14, and 0.13 million in 2013, respectively, leading to a total ΔMort of 1.3 million. Source-oriented CMAQ modeling determined that industrial and residential sources were the two leading sources of ΔMort, contributing to 0.40 (30.5%) and 0.28 (21.7%) million deaths, respectively. Additionally, secondary ammonium ion from agriculture, secondary organic aerosol, and aerosols from power generation were responsible for 0.16, 0.14, and 0.13 million deaths, respectively. A 30% ΔMort reduction in China requires an average of 50% reduction of PM2.5 throughout the country and a reduction by 62%, 50%, and 38% for the Beijing–Tianjin–Hebei, Jiangsu–Zhejiang–Shanghai, and Pearl River Delta regions, respectively. Reducing PM2.5 to the CAAQS grade II standard of 35 μg m–3 would only lead to a small reduction in mortality, and a more stringent standard of <15 μg m–3 would be needed for more remarkable reduction of ΔMort.
•This is the largest evaluation on the effects of PM2.5 constituents on cause-specific mortality in China.•PM2.5 constituents were significantly associated with mortality risk in China, with largest ...effect for OC.•Those with cardiovascular disease, females, the elderly, and illiterates were more vulnerable to PM2.5 constituents.•Higher mortality risks of PM2.5 constituents were generally observed in residents in the South and urban communities.
Fine particulate matter (with aerodynamic diameter ≤2.5 µm, PM2.5) causes huge disease burden worldwide. However, evidence is still inadequate and inconsistent on the relationships between PM2.5 constituents and mortality, especially in low resource settings.
To evaluate the impact of PM2.5 constituents on cause-specific mortality in China.
We obtained daily mortality data for 161 communities in 2011–2013 from the Disease Surveillance Point system in China. Daily concentrations of major PM2.5 constituents, including organic carbon (OC), elemental carbon (EC), sulphate (SO42-), nitrate (NO3-) and ammonium (NH4+), were estimated by using the modified Community Multiscale Air Quality model. For each community, we applied quasi-Poisson regression and polynomial distributed lag models to estimate the effects of PM2.5 constituents on cause-specific mortality. Then, the pooled effect estimates were calculated by a random-effect meta-analysis based on the restricted maximum likelihood estimation. Stratification analyses were performed by region, gender, age group and education level to identify the vulnerable populations.
Each interquartile range change of EC, OC, SO42-, NO3- and NH4+ at lag 0–3 day was associated with increments in non-accidental mortality of 0.45% (95%CI: 0.21, 0.69), 1.43% (0.97, 1.89), 0.71% (0.28, 1.15), 0.70% (0.10, 1.30) and 0.95% (0.39, 1.51), respectively. The associations were stronger for the deaths from cardiovascular disease and myocardial infarction, the elderly, illiterates, and people living in the South region.
Our findings suggest positive associations between PM2.5 constituents and cause-specific mortality, particularly for myocardial infarction.
Source contributions to fine airborne particulate matter with aerodynamic diameters <2.5μm (PM2.5) during 2013 were determined for 25 Chinese provincial capitals and municipalities using a ...source-oriented version of the Community Multiscale Air Quality (CMAQ) model. Based on the hierarchical clustering analysis of the observed PM2.5 concentrations, the 25 cities were categorized into nine groups. Generally, annual PM2.5 concentrations were highest in the cities in the north (81–154μgm−3) and lowest in the cities close to seas in the south and east (27–57μgm−3). Seasonal PM2.5 observations in the cities were generally higher in winter than in the other seasons. Industrial or residential sources were predicted to be the largest contributor to PM2.5 for all the city groups, with annually fractional contributions of 25.0%–38.6% and 9.6%–27%, respectively. The annual contributions from power plants, agriculture NH3, windblown dust, and secondary organic aerosol (SOA) for the city groups were 8.7%–12.7%, 9.5%–12%, 6.1%–12.5%, and 5.4%–15.5%, respectively. Meanwhile, the annual contributions from transportation, sea salt, and open burning were relatively low (<8%, <2%, and <6%, respectively). Secondary PM2.5 accounted for 47%–63% of total annual PM2.5 concentrations in the cities and contributed to as much as 70% of daily PM2.5 concentrations on PM2.5 pollution days (daily concentrations>75μgm−3). Industrial or residential sources were generally the largest contributor on PM2.5 pollution days for all the city groups in each season, except that open burning, SOA, and windblown dust could be more important on some days, particularly in spring. The results of this study would be helpful to develop measures to reduce annual PM2.5 concentrations and the number of PM2.5 pollution days for different regions of China.
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•Source contributions to PM2.5 in 2013 at 25 major Chinese cities were determined.•Industrial and residential activities were predicted to be the largest contributor.•On high pollution days, as much as 70% of PM2.5 were due to secondary inorganics.•Industries have higher fractions of secondary inorganics than residential sources.
Polycyclic aromatic hydrocarbons (PAHs) in the environment are of significant concerns due to their high toxicity to human health. PAHs measurements at limited air quality monitoring stations alone ...are insufficient to gain a complete understanding of ambient levels and public exposure of PAHs in China. This study simulated the concentrations of PAHs in China, identified the source contributions, and estimated the health risks. Anthropogenic emissions of 16 priority PAHs directly associated with health risks were generated from the global high-resolution PKU-FUEL-2007 inventory. Open biomass burning emissions were generated from the Fire Inventory from NCAR (FINN). PAHs concentrations in January, April, July, and October 2013 were simulated using the Community Multiscale Air Quality (CMAQ) model after incorporation of chemistry, partitioning, and deposition of PAHs. Predicted PAHs were in good agreement with seasonal and annual averaged observations from previous studies. The surface concentrations of 16-PAHs were higher in winter, with population weight average of 0.8 μg/m3 and peak value of 2.0 μg/m3 in urban areas in the North China Plain (NCP) and the Yangtze River Delta (YRD). Summer and spring exhibited lower concentrations of approximately 0.2 μg/m3 in most areas. The most important sources to PAHs were biomass burning and coal combustion in winter and industrial processes and oil and gas activities in summer. The cancer risk due to inhalation exposure of naphthalene (NAPH) and seven carcinogenic PAHs was significant, with the incremental lifetime cancer risk (ILCR) of >5 × 10−4 in many urban and industrial areas. Exposure to PAHs was estimated to result in 15,198 excess lifetime cancer cases in China. Oil and gas burning associated with transport, residential and commercial activities were major contributors to ILCR in China. Coal combustion was predominant in Shanxi but less important in other regions.
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•Sources and health risks of 16 priority PAHs in China were estimated in 2013.•Temporally higher PAHs in winter and spatially higher PAHs in north China.•Coal combustion, oil and gas related activities are major sources of PAHs.•ILCR of PAHs exceeds 5 × 10−4 in many urban and industrial areas.•Exposure to PAHs results in approximately 15,198 excess lifetime cancer cases.
Ammonia (NH3) is the predominant alkaline gas in the atmosphere contributing to formation of fine particlesa leading environmental cause of increased morbidity and mortality worldwide. Prior ...findings suggest that NH3 in the urban atmosphere derives from a complex mixture of agricultural (mainly livestock production and fertilizer application) and nonagricultural (e.g., urban waste, fossil fuel-related emissions) sources; however, a citywide holistic assessment is hitherto lacking. Here we show that NH3 from nonagricultural sources rivals agricultural NH3 source contributions in the Shanghai urban atmosphere. We base our conclusion on four independent approaches: (i) a full-year operation of a passive NH3 monitoring network at 14 locations covering urban, suburban, and rural landscapes; (ii) model-measurement comparison of hourly NH3 concentrations at a pair of urban and rural supersites; (iii) source-specific NH3 measurements from emission sources; and (iv) localized isotopic signatures of NH3 sources integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates of ambient NH3. Results indicate that nonagricultural sources and agricultural sources are both important contributors to NH3 in the urban atmosphere. These findings highlight opportunities to limit NH3 emissions from nonagricultural sources to help curb PM2.5 pollution in urban China.
A high-resolution inventory of primary atmospheric pollutants from coal-fired power plants in Shaanxi in 2012 was built based on a detailed database compiled at unit level involving unit capacity, ...boiler size and type, commission time, corresponding control technologies, and average coal quality of 72 power plants. The pollutants included SO2, NOx, fine particulate matter (PM2.5), inhalable particulate matter (PM10), organic carbon (OC), elemental carbon (EC), carbon monoxide (CO) and non-methane volatile organic compounds (NMVOC). Emission factors for SO2, NOx, PM2.5 and PM10 were adopted from standardized official promulgation, supplemented by those from local studies. The estimated annual emissions of SO2, NOx, PM2.5, PM10, EC, OC, CO and NMVOC were 152.4, 314.8, 16.6, 26.4, 0.07, 0.27, 64.9 and 2.5kt, respectively. Small units (<100MW), which accounted for ~60% of total unit numbers, had less coal consumption but higher emission rates compared to medium (≥100MW and <300MW) and large units (≥300MW). Main factors affecting SO2, NOx, PM2.5 and PM10 emissions were decontamination efficiency, sulfur content and ash content of coal. Weinan and Xianyang were the two cities with the highest emissions, and Guanzhong Plain had the largest emission density. Despite the projected growth of coal consumption, emissions would decrease in 2030 due to improvement in emission control technologies and combustion efficiencies. SO2 and NOx emissions would experience significant reduction by ~81% and ~84%, respectively. PM2.5, PM10, EC and OC would be decreased by ~43% and CO and NMVOC would be reduced by ~16%.
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•Emission inventory of pollutants from coal-fired power plants in Shaanxi was created for 2012.•Emission factors from official promulgation were adopted for SO2, NOx, PM2.5 and PM10.•Decontamination efficiency, coal quality and unit capacity in reality were used and their effects were analyzed.•SO2, NOx, PM2.5 and PM10 from coal-fired power plants have decreased since 2012.
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