Spatiotemporal characteristics of PM2.5 and ozone concentrations in Chinese urban clusters

Long-term exposure to PM2.5 compositions and O3 and their interactive effects on DNA methylation of peripheral brain-derived neurotrophic factor promoter

This study examined the associations of long-term exposure to ambient fine particulate matter (PM2.5) compositions/ozone with methylation of peripheral brain-derived neurotrophic factor (BDNF) promoters. A total of 101 participants were recruited from a cohort in Shijiazhuang, Hebei province, China. They underwent baseline and follow-up surveys in 2011 and 2015. DNA methylation levels were detected by bisulfite-PCR amplification and pyrosequencing. Participants' three-year average levels of PM2.5 compositions and ozone were estimated. Bayesian kernel machine regression (BKMR) models were used to examine the joint effects of pollutants on methylation levels. Exposure to PM2.5 compositions and ozone mixtures at the 75th percentile was associated with increased methylation levels at CpG2 of BDNF promoter (203%, 95% CI: 89, 316) than the lowest level of exposure, and sulfate dominated the effect in the BKMR models.Our findings provide clues to the epigenetic mechanisms for the associations of PM2.5 compositions and ozone with BDNF.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002-2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality-Integrated Source Apportionment Method (CMAQ-ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21-40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> -20 μg/m3) after 2011 due to pollution control measures.

Spatio-temporal variations of PM2.5 and O3 in China during 2013-2021: Impact factor analysis

Fine particulate matter (PM2.5) and ozone (O3) pollution are regarded as significant secondary air pollutants. The PM2.5 in most regions in China declined, and the decreasing rate in January was lower than the annual average. However, O3 concentration showed a steady increasing trend in most regions, and the increasing rate in July was slightly higher than the annual average. In particular, the annual average PM2.5 concentration and excess rate showed an increasing trend on the northern slope of the Tianshan Mountains. Conversely, O3 concentrations had shown a consistent increasing trend, exceeding the annual average limit of 100 μg/m3. Surface pressure exhibited positive correlations with PM2.5 in winter and O3 in summer across urban agglomerations. Moreover, soil temperature at different depths explained over 30% of the variations in PM2.5 and O3 in the Chengdu-Chongqing, Beijing-Tianjin-Hebei, and Lanzhou-Xining urban agglomerations. In winter, relative humidity demonstrated a positive correlation with urban agglomerations in northeast and northwest China, regions characterized by dry climates. During the COVID-19 period, the impacts of meteorological factors and soil temperature on PM2.5 and O3 differed significantly compared to preceding and subsequent periods. Notably, during the winter of 2020, the Harbin-Changchuan urban agglomeration exhibited a notable transition, as O3 and PM2.5 concentrations shifted from a strong negative correlation to a robust positive correlation. This remarkable shift, with deviations explained up to 60%, represents a unique phenomenon worth emphasizing in the study's findings.

Cooperative simultaneous inversion of satellite-based real-time PM2.5 and ozone levels using an improved deep learning model with attention mechanism

Ground-level fine particulate matter (PM_2.5) and ozone (O₃) are air pollutants that can pose severe health risks. Surface PM_2.5 and O₃ concentrations can be monitored from satellites, but most retrieval methods retrieve PM_2.5 or O₃ separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China spanning 2014-2021, we found a strong relationship between PM_2.5 and O₃ with distinct spatiotemporal characteristics. Thus, in this study, we propose a new deep learning model called the Simultaneous Ozone and PM_2.5 inversion deep neural Network (SOPiNet), which allows for daily real-time monitoring and full coverage of PM_2.5 and O₃ simultaneously at a spatial resolution of 5 km. SOPiNet employs the multi-head attention mechanism to better capture the temporal variations in PM_2.5 and O₃ based on previous days' conditions. Applying SOPiNet to MODIS data over China in 2022, using 2019-2021 to construct the network, we found that simultaneous retrievals of PM_2.5 and O₃ improved the performance compared with retrieving them independently: the temporal R² increased from 0.66 to 0.72 for PM_2.5, and from 0.79 to 0.82 for O₃. The results suggest that near-real time satellite-based air quality monitoring can be improved by simultaneous retrieval of different but related pollutants. The codes of SOPiNet and its user guide are freely available online at https://github.com/RegiusQuant/ESIDLM.

Emission of VOCs from service stations in Beijing: Species characteristics and pollutants co-control based on SOA and O3

Currently, air pollution is primarily characterized by PM_2.5 and O₃. Therefore, the co-control of PM_2.5 and O₃ has become an important task of atmosphere pollution prevention and control in China. However, few studies have been conducted on the emissions from vapor recovery and processes, which is an important source of VOCs. This paper analyzed the VOC emissions of three vapor process technologies in service stations and first proposed key pollutants for priority control based on the coordinated reactivity of O₃ and SOA. The concentration of VOCs emitted from the vapor processor was 3.14-9.95 g m^-3, compared to 631.2-717.8 g m^-3 for uncontrolled vapor. Alkanes, alkenes, and halocarbons accounted for a high proportion of the vapor both before and after control. Among the emissions, i-pentane, n-butane, and i-butane were the most abundant species. Then, the species of OFP and SOAP were calculated through the maximum incremental reactivity (MIR) and fractional aerosol coefficient (FAC). The average source reactivity (SR) value of the VOC emissions from three service stations was 1.9 g g^-1, while the OFP ranged from 8.2 to 13.9 g m^-3 and SOAP ranged from 0.18 to 0.36 g m^-3. By considering the coordinated chemical reactivity of O₃ and SOA, a comprehensive control index (CCI) was proposed for the control of key pollutant species that have multiplier effects on environment. For adsorption, trans-2-butene and p-xylene were the key co-control pollutants, while toluene and trans-2-butene were the most important for membrane and condensation + membrane control. A 50% emission reduction of the top two key species that emission account for 4.3% averagely will reduce O₃ by 18.4% and SOA by 17.9%.

Perchlorate in fine particulate matter in Shenzhen, China, and implications for human inhalation exposure

The wide application of perchlorate in military and aerospace industries raises potential exposure risks for humans. Previous studies have mainly focused on perchlorate in drinking water, foodstuffs and dust, while its exposure in fine particulate matter (PM_2.5) has received less attention. Thus, we investigated its concentrations and temporal variability in PM_2.5 from October 2020 to September 2021 in Shenzhen, southern China. We also assessed the native population's intake and uptake of perchlorate in PM_2.5 via inhalation. Measured PM_2.5 concentrations in samples from Shenzhen ranged from 2.0 to 91.9 μg m^-3. According to air quality guidelines proposed by the World Health Organization, 12.7% of all the samples exceeded interim target 1 (> 35 μg m^-3), and only 37.3% met interim target 3 (< 15 μg m^-3). Logistic regression analysis showed that perchlorate concentrations positively correlated with the PM_2.5 concentrations and negatively correlated with precipitation. The median estimated daily intake (EDI) was highest for infants (0.029 ng kg^-1 day^-1), and both EDIs and estimated daily uptakes (EDUs) gradually decreased with age. All the EDIs and EDUs were below the reference dose provided by the US National Academy of Sciences (NAS), indicating that exposure to perchlorate in PM_2.5 posed negligible health risks for Shenzhen residents. However, the exposure of infants and specific groups who tend to be more highly exposed than average still warrants attention.

Driving Forces of Meteorology and Emission Changes on Surface Ozone in the Huaihe River Basin, China

Surface ozone (O3) pollution in China has become a serious environmental problem in recent years. In the present study, we targeted the HRB, a large region located in China's north-south border zone, to assess the driving forces of meteorology and emission changes on surface ozone. A Kolmogorov-Zurbenko (KZ) filter method was performed on the maximum daily average 8-h (MDA8) concentrations of ozone in the HRB during 2015-2020 to decompose the original time series. The findings demonstrated that the short-term (O3ST), seasonal (O3SN), and long-term components (O3LT) of MDA8 O3 variations accounted for 34.2%, 56.1%, and 2.9% of the total variance, respectively. O3SN has the greatest influence on the daily variation in MDA8 O3, followed by O3ST. In coastal cities, the influence of O3ST was enhanced. The influence of O3SN was stronger in the northwestern HRB. Air temperature is the prevailing variable that influences the photochemical formation of ozone. A clear phase lag (7-34 days) of the baseline component between MDA8 O3 and the atmospheric temperature was found in the HRB. Using multiple linear regression, the effect of temperature on ozone was removed. We estimated that the increase in ozone concentration in the HRB was mainly caused by the emission changes (79.4%), and the meteorological conditions made a small contribution (20.6%). This study suggests that reductions in volatile organic compounds (VOCs) will play an important role in further ozone pollution reduction in the HRB.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06345-1.

The characteristics of nano-micron calcite particles/common bacteria complex and its interfacial interaction

Based on the composite pollution of atmospheric microbial aerosol, this paper selects the calcite/bacteria complex as the research object which was prepared by calcite particles and two common strains of bacteria (Escherichia coli, Staphylococcus aureus) in the solution system. The morphology, particle size, surface potential, and surface groups of the complex were explored by modern analysis and testing methods, with an emphasis on the interfacial interaction between calcite and bacteria. The SEM, TEM, and CLSM results showed that the morphology of the complex could be divided into three types: bacteria adhering to the surface or edge of micro-CaCO₃, bacteria aggregating with nano-CaCO₃, and single nano-CaCO₃ wrapping bacteria. The complex's particle size was about 2.07 ~ 192.4 times larger than the original mineral particles, and the nano-CaCO₃/bacteria complex's particle size variation was caused by the fact that nano-CaCO₃ has agglomeration in solution. The surface potential of the micro-CaCO₃/bacteria complex (isoelectric point pH = 3.0) lies between micro-CaCO₃ and bacteria, while the surface potential of the nano-CaCO₃/bacteria complex (isoelectric point pH = 2.0) approaches the nano-CaCO₃. The complex's surface groups were based primarily on the infrared characteristics of calcite particles, accompanied by the infrared characteristics of bacteria, displaying the interfacial interaction from the protein, polysaccharides, and phosphodiester groups of bacteria. The interfacial action of the micro-CaCO₃/bacteria complex is mainly driven by electrostatic attraction and hydrogen bonding force, while the nano-CaCO₃/bacteria complex is guided by surface complexation and hydrogen bonding force. The increase in the β-fold/α-helix ratio of the calcite/S. aureus complex indicated that the secondary structure of bacterial surface proteins was more stable and the hydrogen bond effect was strong than the calcite/E. coli complex. The findings are expected to provide basic data for the mechanism research of atmospheric composite particles closer to the real environment.

Underestimation of biomass burning contribution to PM2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China

Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM_2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM_2.5, PM_2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K⁺ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K⁺ with K⁺_BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM_2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.

Urban Surface Ozone Concentration in Mainland China during 2015-2020: Spatial Clustering and Temporal Dynamics

Urban ozone (O₃) pollution in the atmosphere has become increasingly prominent on a national scale in mainland China, although the atmospheric particulate matter pollution has been significantly reduced in recent years. The clustering and dynamic variation characteristics of the O₃ concentrations in cities across the country, however, have not been accurately explored at relevant spatiotemporal scales. In this study, a standard deviational ellipse analysis and multiscale geographically weighted regression models were applied to explore the migration process and influencing factors of O₃ pollution based on measured data from urban monitoring sites in mainland China. The results suggested that the urban O₃ concentration in mainland China reached its peak in 2018, and the annual O₃ concentration reached 157 ± 27 μg/m³ from 2015 to 2020. On the scale of the whole Chinese mainland, the distribution of O₃ exhibited spatial dependence and aggregation. On the regional scale, the areas of high O₃ concentrations were mainly concentrated in Beijing-Tianjin-Hebei, Shandong, Jiangsu, Henan, and other regions. In addition, the standard deviation ellipse of the urban O₃ concentration covered the entire eastern part of mainland China. Overall, the geographic center of ozone pollution has a tendency to move to the south with the time variation. The interaction between sunshine hours and other factors (precipitation, NO₂, DEM, SO₂, PM_2.5) significantly affected the variation of urban O₃ concentration. In Southwest China, Northwest China, and Central China, the suppression effect of vegetation on local O₃ was more obvious than that in other regions. Therefore, this study clarified for the first time the migration path of the gravity center of the urban O₃ pollution and identified the key areas for the prevention and control of O₃ pollution in mainland China.

Maize yield reduction and economic losses caused by ground-level ozone pollution with exposure- and flux-response relationships in the North China Plain

Ground-level ozone (O₃) has negative effects on agricultural crops. Maize is an important grain crop in China. The North China Plain (NCP) serves as the major crops' production area of China and experiences severe ozone pollution. Using the ground-level ozone simulated by an atmospheric chemistry transport model (WRF-Chem), we quantified the yield reduction and economic losses of maize during 2015-2018 over NCP based on exposure-response AOT40 (accumulation of hourly O₃ concentration exceed 40 ppb) and flux-response POD₆ (phytotoxic dose of ozone over 6 nmol m^-2 s^-1). Results showed that the ozone concentration, AOT40, and POD₆ clearly increased from 2015 to 2018 in growing season of maize over NCP. The four-year annual mean ozone concentration, AOT40, and POD₆ were 0.055 ppm, 18.02 ppm h, and 5.02 mmol m^-2, respectively. At county level, the relative loss of maize yield (MRYL) based on AOT40 and POD₆ had clearly spatio-temporal differences in NCP. The average MRYLs of AOT40 and of POD₆ from 2015 to 2018 were 10.4% and 21.4%, respectively, and these reductions were associated with 2399 million and 5637 million US dollars, respectively. This study suggests that surface ozone increased the yield losses of maize, and indicates that further reductions in ozone concentrations can enhance the food security in China.