China National Environmental Monitoring Center Research Articles

A meta-analysis and experimental survey of heavy metals pollution in agricultural soils

Heavy metal (HM) pollution in agricultural soils represents a hidden danger to food security worldwide. In this paper, the spatio-temporal trends of heavy metals from eight countries and 50 soil samples from agricultural farmland were evaluated through a combination of field surveys and meta-analysis to provide a comprehensive report on heavy metal pollution. The soil samples were analysed using inductively coupled plasma–mass spectrometry (ICP-MS) (Perkin Elmer Nixon 300Q). The contamination factor (CF) and pollution load index (PLI), and diagnostic tests on the extracted data were calculated. The results of the CF in the soils indicate extreme contamination for Cr, suggesting ecotoxicological effects, while the PLI values range from baseline to moderate pollution for Cd, Hg, Cu, Zn, and Ni, except for Cr, which shows very high pollution, suggesting that the soils have undergone some form of deterioration. The meta-analysis results of the 50 reviewed articles published between 2010 and 2023 showed increasing trends for all the HMs. The weighted mean values of Cd, Cr, Hg, Cu, Zn, As, and Ni were in the range of 0.0-222.7, 0.08-289.2, 0.03-193, 2.94-198.1, 0.0-771.1, 0.0-231, and 1.71-99.75.6 mg/kg, respectively. The mean values of Cd, Hg, Zn and As exceeded two to three times the values of China National Environmental Monitoring Centre (CNEMC) European Union's most cited guideline (MEF), and the rock crust guideline. The results of the correlation matrix heatmap revealed a highly positive correlation between Cr and Ni (R2 = 0.66), suggesting that these elements have the same source and are likely prevalent in agricultural soils. The spatial origin of the publications reveals that 82% of the studies were from China followed by South Africa and Italy accounting for 4% respectively while Nigeria, Egypt, Morocco, Iran, and Turkey account for 2% each. The findings of this study have important implications for environmental regulation on agricultural food protection from heavy metal pollution. Unlike previous meta-analysis studies which often adopt a “silos” method, this study highlights a nexus approach that integrates both meta-analysis and experimental studies which could establish a more comprehensive understanding of heavy metal pollution in agricultural soils.

An Evaluation of the Influence of Meteorological Factors and a Pollutant Emission Inventory on PM2.5 Prediction in the Beijing–Tianjin–Hebei Region Based on a Deep Learning Method

In this study, a Long Short-Term Memory (LSTM) network approach is employed to evaluate the prediction performance of PM2.5 in the Beijing–Tianjin–Hebei region (BTH). The proposed method is evaluated using the hourly air quality datasets from the China National Environmental Monitoring Center, European Center for Medium-range Weather Forecasts ERA5 (ECMWF-ERA5), and Multi-resolution Emission Inventory for China (MEIC) for the years 2016 and 2017. The predicted PM2.5 concentrations demonstrate a strong correlation with the observed values (R2 = 0.871–0.940) in the air quality dataset. Furthermore, the model exhibited the best performance in situations of heavy pollution (PM2.5 > 150 μg/m3) and during the winter season, with respective R2 values of 0.689 and 0.915. In addition, the influence of ECMWF-ERA5’s hourly meteorological factors was assessed, and the results revealed regional heterogeneity on a large scale. Further evaluation was conducted by analyzing the chemical components of the MEIC inventory on the prediction performance. We concluded that the same temporal profile may not be suitable for addressing emission inventories in a large area with a deep learning method.

Nighttime ozone excess days and the associated meteorological conditions in the North China Plain from 2015 to 2022

We examined the spatial and temporal variations of nighttime ozone (O3) excess days (NOEDs) in the North China Plain (NCP) during 2015–2022 by using the observed O3 concentrations from the China National Environmental Monitoring Center network. The NOEDs were defined as those with any 1-h average O3 concentration at night (20:00 to 06:00 local time) exceeding 200 μg m−3. The observations showed that the annual frequencies of NOEDs averaged over the 57 cities in the NCP were 1.56, 1.72, 6.23, 6.53, 8.84, 5.93, 5.07, and 6.86 days in 2015, 2016, 2017, 2018, 2019, 2020, 2021, and 2022, respectively, with a linear increasing trend of 0.66 d y−1. Using the K-means clustering method, two typical regional NOEDs types in the NCP were identified. Type1 had the highest frequencies of NOEDs in the southwest of NCP, while Type2 had the highest frequencies in the central NCP region. These two types contributed to 53.5% and 46.5% of the regional NOEDs in NCP, respectively. Compared with the regional non-NOEDs (with nighttime O3 did not exceed but daytime O3 exceeded O3 air quality standard), both Type1 and Type2 NOEDs generally had higher temperature, lower relative humidity, and higher planetary boundary height in both afternoon and night, favoring the production and accumulation of O3 in the afternoon as well as the persistent high O3 at night. Corresponding weather patterns were also identified. These results have important implications for emission control strategies during NOEDs. Emission control measures can be applied once the dominant circulation patterns have been predicted.

Comment on “Transport of substantial stratospheric ozone to the surface by a dying typhoon and shallow convection” by Chen et al. (2022)

Abstract. Chen et al. (2022) analyzed the event of rapid nocturnal O3 enhancement (NOE) observed on 31 July 2021 at the surface level in the North China Plain and proposed transport of substantial stratosphere ozone to the surface by Typhoon In-fa followed by downdraft of shallow convection as the mechanism of the NOE event. The analysis seems to be valid from the viewpoint of atmospheric physics. This comment revisits the NOE phenomenon on the basis of the China National Environmental Monitoring Center (CNEMC) network data used in Chen et al. (2022), together with the CNEMC data from Zibo (ZB) and O3, NOx, PAN (peroxyacetic nitric anhydride), and VOC (volatile organic compound) data from the Zibo supersite operated by the China Research Academy of Environmental Sciences (CRAES). We found (a) Ox (O3 + NO2) levels during the NOE period approaching those of O3 during 14:00–17:00 LT, (b) levels of PAN and the relationship between O3 and PAN consistent with dominance of chemical and physical processes within the boundary layer, and (c) estimated photochemical ages of air mass shorter than 1 d and showing no drastic increases during the NOE. We argue that the NOE was not caused by typhoon-induced stratospheric intrusion but originated from fresh photochemical production in the lower troposphere. Our argument is well supported by the analysis of atmospheric transport as well as ground-based remote sensing data.

Objectively measured the impact of ambient air pollution on physical activity for older adults

BackgroundAir pollution poses a significant health risk to the human population, especially for vulnerable groups such as the elderly, potentially discouraging their engagement in physical activity. However, there is a lack of sufficient objective and longitudinal data in current research on how air pollution affects physical activity among older adults. With these gaps, we aimed to explore the relationship between air pollution and objective measurement-based physical activity among older adults by engaging in a longitudinal study design.MethodsA total of 184 older adults were recruited from three cities with varying levels of air quality. Mean daily minutes of physical activity were measured with 7 consecutive days of accelerometer monitoring (ActiGraph GT3X-BT). Corresponding air pollution data including daily PM2.5 (µg/m3), PM10 (µg/m3) and air quality index (AQI) were sourced from the China National Environmental Monitoring Centre at monitor locations close to older adults’ addresses. Associations between air quality and physical activity were estimated using a fixed effect model, adjusting for average daytime temperature, rain, age and weight.ResultsAQI and PM2.5 were observed to exhibit significant, inverse, and linear associations with mean daily walk steps, minutes of light physical activity (LPA), moderate physical activity (MPA) and moderate-to-vigorous physical activity (MVPA) in the single variable models. A one-level increase in AQI corresponded to a decline in 550.04 steps (95% [CI] = -858.97, -241.10; p < 0.001), 10.43 min (95% [CI] = -17.07, -3.79; p < 0.001), 4.03 min (95% [CI] = -7.48, -0.59; p < 0.001) and 4.16 min (95% [CI] = -7.77, -0.56; p < 0.001) in daily walking steps, LPA, MPA, and MVPA, respectively. A one-level increase in PM2.5 correlated with a decline in daily walk steps, LPA, MPA and MVPA by 361.85 steps (95% [CI] = -516.53, -207.16; p < 0.001), 8.97 min (95% [CI] = -12.28, -5.66; p < 0.001), 3.73 min (95% [CI] = -5.46, -2.01; p < 0.001,) and 3.79 min (95% [CI] = -5.59, -1.98; p < 0.001), respectively. However, PM10 displayed a significant negative association exclusively with LPA, with one-level increase in PM10 resulting in a 3.7-minute reduction in LPA (95% [CI] = -6.81, -0.59, p < 0.05).ConclusionAir pollution demonstrates an inverse association with physical activity levels among older adults, potentially discouraging their engagement in physical activity. Different air quality indicators may exert varying impacts on physical activity. Future studies are warranted to enhance policy interventions aimed at reducing air pollution and promoting physical activity.

Studies on regional ozone formation sensitivities and transport with higher spatiotemporal resolutions in a stereoscopic dimension: GEMS and vertical observations

Currently, ozone pollution is one of the key environmental concerns, and to provide more effective strategies for ozone control, this paper proposes the use of the Geostationary Environmental Monitoring Spectrometer (GEMS) in conjunction with MAX-DOAS for observations and ozone sensitivity analysis. Compared to traditional polar-orbiting satellites, GEMS, launched by South Korea in 2019, offers superior spatiotemporal resolution. However, there is a lack of ground validation for GEMS data related to ozone and its precursors. In this study, we conducted validation in the Jing-Jin-Ji (Beijing-Tianjin-Hebei) region using two typical MAX-DOAS sites and the China National Environmental Monitoring Center (CNEMC) sites, confirming the accuracy of GEMS data. Analysis of the seasonal horizontal distribution results from GEMS and vertical distribution results from MAX-DOAS in 2022 reveals that the concentrations of NO2, HCHO, O3, and ozone sensitivity not only display seasonality and regional variations but also exhibit distinct characteristics at different altitudes and times, influenced by local climatic conditions, human activities, and topography. When formulating ozone control policies, it becomes imperative to consider factors such as time, regional characteristics, and seasonality. Comparisons between daily results from TROPOMI and GEMS indicate that polar-orbiting satellites may overlook high-pollution periods within a single day, and their measurements may not provide a comprehensive representation of an entire day's data. Consequently, relying solely on polar-orbiting satellite data for shaping ozone prevention and control policies may inadvertently encourage ozone formation during specific time periods, rendering these policies ineffective. Therefore, leveraging GEMS is essential for the development of comprehensive, around-the-clock ozone control policies. Finally, we used monitoring data from Beijing on October 6, 2022, to illustrate how the combination of GEMS and MAX-DOAS enables three-dimensional monitoring of pollutant transport processes on an hourly scale.

Identification of O3 Sensitivity to Secondary HCHO and NO2 Measured by MAX-DOAS in Four Cities in China

This study analyzed the differences in ozone (O3) sensitivity in four different urban areas in China from February 2019 to January 2020 based on data on various near-surface pollutants from passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) sites and nearby China National Environmental Monitoring Center (CNEMC) sites. Across the four cities, the nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations varied seasonally. Xianghe consistently displayed the lowest NO2 levels, suggesting reduced emissions compared to other cities. Guangzhou, a city with a robust economy and a high level of vehicle ownership, exhibited higher concentrations in spring. Summer brought elevated HCHO levels in Guangzhou, Xianghe, and Shenyang due to intensified photochemical processes. Autumn and winter showed higher HCHO concentrations in Guangzhou and Xianghe compared to Lanzhou and Shenyang. Overall, Guangzhou recorded the highest annual averages, due to its developed economy, while Xianghe’s lower NO2 levels were offset by the elevated HCHO due to higher O3 values. The analysis delved into primary and secondary HCHO sources across seasons and used carbon monoxide (CO) and O3 data. Xianghe showcased the dominance of secondary sources in summer and autumn, while Lanzhou was characterized by primary dominance throughout the year. Shenyang mirrored Xianghe’s evolution due to industrial emissions. In Guangzhou, due to the high levels of vehicular traffic and sunlight conditions, secondary sources predominantly influenced HCHO concentrations. These findings highlight the interplay between primary and secondary emissions in diverse urban settings. This study explored O3 sensitivity variations across seasons. Xianghe exhibited a balanced distribution among volatile organic compound (VOC)-limited conditions, nitrogen oxide (NOx)-limited conditions, and transitional influences. Lanzhou was mainly affected by VOC-limited conditions in winter and NOx-limited conditions in other seasons. Shenyang’s sensitivity varied with the seasons and was primarily influenced by transitions between VOCs and NOx in autumn and NOx-limited conditions otherwise. Guangzhou experienced varied influences. During periods of high O3 pollution, all regions were affected by NOx-limited conditions, indicating the necessity of NOx monitoring in these areas, especially during summer in all regions and during autumn in Xianghe and Guangzhou.

Analysis of Ozone Formation Sensitivity in Chinese Representative Regions Using Satellite and Ground-Based Data

O3 poses a significant threat to human health and the ecological environment. In recent years, O3 pollution has become increasingly serious, making it difficult to accurately control O3 precursor emissions. Satellite indicator methods, such as the FNR (formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2 ratio)), provide an effective way to identify ozone pollution control areas on a large geographical scale due to their simple acquisition of datasets. This can help determine the primary factors contributing to O3 pollution and assist in managing it. Based on TROPOMI data from May 2018 to December 2022, combined with ground-based monitoring data from the China National Environmental Monitoring Centre, we explored the uncertainty associated with using the HCHO/NO2 ratio (FNR) as an indicator in ozone control area determination. We focused on the four representative regions in China: Jing-Jin-Ji-Lu-Yu (JJJLY), Jiang-Zhe-Hu-Wan (JZHW), Chuan-Yu (CY), and South China. By using the statistical curve-fitting method, we found that the FNR thresholds were 3.5–5.1, 2.0–4.0, 2.5–4.2, and 1.7–3.5, respectively. Meanwhile, we analyzed the spatial and temporal characteristics of the HCHO, NO2, and O3 control areas. The HCHO concentrations and NO2 concentrations had obvious cyclical patterns, with higher HCHO column densities occurring in summer and higher NO2 concentrations in winter. These high values always appeared in areas with dense population activities and well-developed economies. The distribution characteristics of the ozone control areas indicated that during O3 pollution periods, the urban areas with industrial activities and high population densities were primarily controlled by VOCs, and the suburban areas gradually shifted from VOC-limited regimes to transitional regimes and eventually reverted back to VOC-limited regimes. In contrast, the rural and other remote areas with relatively less development were mainly controlled by NOx. The FNR also exhibited periodic variations, with higher values mostly appearing in summer and lower values appearing in winter. This study identifies the main factors contributing to O3 pollution in different regions of China and can serve as a valuable reference for O3 pollution control.

The Impact of Air Pollution Controls on Health and Health Inequity Among Middle-Aged and Older Chinese: Evidence From Panel Data.

We evaluated the long-term effects of air pollution controls on health and health inequity among Chinese >45 years of age. Data were derived from the China Health Aging and Retirement Longitudinal Survey and the China National Environmental Monitoring Centre. Decreases in PM2.5 and PM10 were scaled to measure air quality controls. We used a quasi-experimental design to estimate the impact of air quality controls on self-reported health and health inequity. Health disparities were estimated using the concentration index and the horizontal index. Air pollution controls significantly improved self-reported health by 20% (OR 1.20, 95% CI, 1.02-1.42). The poorest group had a 40% (OR 1.41, 95% CI, 0.96-2.08) higher probability of having excellent self-reported health after air pollution controls. A pro-rich health inequity was observed, and the horizontal index decreased after air pollution controls. Air pollution controls have a long-term positive effect on health and health equity. The poorest population are the main beneficiaries of air pollution controls, which suggests policymakers should make efforts to reduce health inequity in air pollution controls.

Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey

BackgroundHypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association.MethodsA total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele.ResultsA total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association.ConclusionsThis study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.

High Spatial Resolution Ozone Profiles Retrieved from the First Chinese Ultraviolet–Visible Hyperspectral Satellite Instrument

Understanding the vertical distribution of ozone is crucial when assessing both its horizontal and vertical transport, as well as when analyzing the physical and chemical properties of the atmosphere. One of the most effective ways to obtain high spatial resolution ozone profiles is through satellite observations. The Environmental Trace Gases Monitoring Instrument (EMI) deployed on the Gaofen-5 satellite is the first Chinese ultraviolet–visible hyperspectral spectrometer. However, retrieving ozone profiles using backscattered radiance values measured by the EMI is challenging due to unavailable measurement errors and a low signal-to-noise ratio. The algorithm developed for the Tropospheric Monitoring Instrument did not allow us to retrieve 87% of the EMI pixels. Therefore, we developed an algorithm specific to the characteristics of the EMI. The fitting residuals are smaller than 0.3% in most regions. The retrieved ozone profiles were in good agreement with ozonesonde data, with maximum mean biases of 20% at five latitude bands. By applying EMI averaging kernels to the ozonesonde profiles, the integrated stratospheric column ozone and tropospheric column ozone also showed excellent agreement with ozonesonde data. The lower layers (0–7.5 km) of the EMI ozone profiles reflected the seasonal variation in surface ozone derived from the China National Environmental Monitoring Center (CNEMC). However, the upper layers (9.7–16.7 km) of the ozone profiles show different trends, with the ozone peak occurring at an altitude of 9.7–16.7 km in March, 2019. A stratospheric intrusion event in central China from August 11 to 15, 2019, is captured using the EMI ozone profiles, potential vorticity data, and relative humidity data. The increase in the CNEMC ozone concentration showed that downward transport enhanced surface ozone pollution.

The Aggravation of Summertime Nocturnal Ozone Pollution in China and Its Potential Impact on the Trend of Nitrate Aerosols

AbstractTropospheric ozone (O3) concentration continued to increase over past years, thereby becoming a growing environmental concern in China. Most studies have focused on the analysis of daily maximum 8‐hr O3 concentration, while there is still a dearth of investigations of nocturnal O3. Here, by analyzing the data of 1,313 sites from the China National Environmental Monitoring Center, we show a remarkable increase in the nocturnal O3 concentration during summertime of 2015–2019 in most regions of China, revealing an aggravation of nocturnal O3 pollution. Combining with a GeoDetector model and statistical analysis, we clarify that the aggravation of nocturnal O3 pollution is mainly caused by reduction in both ambient nitrogen dioxide (NO2) concentration and wet scavenging in recent years. We further reveal that the increasing O3 may have enhanced the nocturnal particulate nitrate () formation through N2O5 heterogeneous hydrolysis, and thereby driving the variation and long‐term trend of nocturnal .

Spatiotemporal Patterns and Characteristics of PM2.5 Pollution in the Yellow River Golden Triangle Demonstration Area

Improving air quality in the Yellow River Golden Triangle Demonstration Area (YRGTDA) is an important practice for ecological protection and high-quality development in the Yellow River Basin. Preventing and controlling PM2.5 pollution in this region will require a scientific understanding of the spatiotemporal patterns and characteristics of PM2.5 pollution. PM2.5 data from different sources were combined in this study (the annual average of PM2.5 concentrations were obtained from the Atmospheric Composition Analysis Group of Dalhousie University, and the daily PM2.5 concentration data were obtained from the China National Environmental Monitoring Centre). Then, the temporal variation of PM2.5 concentrations at annual, seasonal, and monthly scales, the spatial variation of PM2.5 concentrations, and the variation of PM2.5 pollution classes were analyzed. Results showed that: (1) at the annual scale, the PM2.5 concentrations showed a decreasing trend from 2000 to 2021 in the study area. The variation of PM2.5 concentrations were divided into two different stages. (2) At the seasonal scale, high PM2.5 concentrations occurred mainly in winter, low PM2.5 concentrations occurred in summer. At the monthly scale, PM2.5 concentrations showed a U-shaped variation pattern from January to December each year. (3) The hotspot analysis of the PM2.5 concentrations in the study area showed a cyclical variation pattern. (4) The PM2.5 concentrations exhibited a spatial pattern of high values in the central and low values in the northern and southern parts of YRGTDA. (5) The number of days for different PM2.5 pollution classes from 2015 to 2021 followed the order of Good &gt; Excellent &gt; Light pollution &gt; Moderate pollution &gt; Heavy pollution &gt; Severe pollution in YRGTDA. The results of this study have great theoretical and practical significance because they reveal the spatiotemporal patterns and pollution characteristics of PM2.5 and will lead to the development of scientifically based measures to reasonably prevent and control pollution in YRGTDA.

The impact of mortality underreporting on the association of ambient temperature and PM10 with mortality risk in time series study

Properly analyzing and reporting data remains a challenging task in epidemiologic research, as underreporting of data is often overlooked. The evaluation on the effect of underreporting remains understudied. In this study, we examined the effect of different scenarios of mortality underreporting on the relationship between PM10, temperature, and mortality. Mortality data, PM10, and temperature data in seven cities were obtained from Provincial Center for Disease Control and Prevention (CDC), China Meteorological Data Sharing Service System, and China National Environmental Monitoring Center, respectively. A time-series design with a distributed lag nonlinear model (DLNM) was used to examine the effects of five mortality underreporting scenarios: 1) Random underreporting of mortality; 2) Underreporting is monotonically increasing (MI) or monotonically decreasing (MD); 3) Underreporting due to holiday and weekends; 4) Underreporting occurs before the 20th day of each month, and these underreporting will be added after the 20th day of the month; and 5) Underreporting due to holiday, weekends, MI, and MD. We observed that underreporting at random (UAR) scenario had little effect on the association between PM10, temperature, and daily mortality. However, other four underreporting not at random (UNAR) scenarios mentioned above had varying degrees of influence on the association between PM10, temperature, and daily mortality. Additionally, in addition to imputation under UAR, the variation of minimum mortality temperature (MMT) and attributable fraction (AF) of mortality attributed to temperature in the same imputation scenarios is inconsistent in different cities. Finally, we observed that the pooled excess risk (ER) below MMT was negatively associated with mortality and the pooled ER above MMT was positively associated with mortality. This study showed that UNAR impacted the association between PM10, temperature, and mortality, and potential underreporting should be dealt with before analyzing data to avoid drawing invalid conclusions.

Crop residual burning correlations with major air pollutants in mainland China

Many studies have established the correlation between crop residual burning (CRB) and air pollutants such as particulate matter (PM) pollutants. However, few studies have compared CRB’s correlations with all major air pollutants, including PM with aerodynamic diameters less than 10µm (PM10) and 2.5 µm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO), during open-field CRB seasons. This study monitored daily CRB spots from 2015 to 2016 in China, together with daily concentrations of PM2.5, PM10, CO, SO2, NO2, and 8 h average O3 provided by the China National Environmental Monitoring Center. Temporal changes in air pollutant concentration at the provincial level and spatial contributions of CRB to air pollution at the monitoring-site level were analyzed. The results indicated that the decrease in CRB from 2015 to 2016 probably led to a decrease in the mean air pollutant concentration and maxima; it also probably led to more outliers at the provincial level in the CRB seasons, especially in Heilongjiang, Jilin, and Liaoning. Spatial contributions suggest that the Heilongjiang, Jilin, and Liaoning provinces experienced a regional increase in the concentrations of almost all major air pollutants during the CRB seasons. In Heilongjiang, Jilin, and Liaoning, 67.88%, 72.12%, 80.00%, 77.58%, and 69.09% of the monitoring sites recorded higher concentrations of PM2.5, PM10, NO2, O3 , and CO, respectively, in the winter CRB season of 2015 compared to other periods. In contrast, in other provinces with fewer and more widely distributed CRB spots, only the monitoring sites close to or on CRB spots experienced increases.

Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China.

Variations in marine and terrestrial geographical environments can cause considerable differences in meteorological conditions, economic features, and population density (PD) levels between coastal and inland cities, which in turn can affect the urban air quality. In this study, a five-year (2016–2020) dataset encompassing air monitoring (from the China National Environmental Monitoring Centre), socioeconomic statistical (from the Shandong Province Bureau of Statistics) and meteorological data (from the U.S. National Centers for Environmental Information, National Oceanic and Atmospheric Administration) was employed to investigate the spatiotemporal distribution characteristics and underlying drivers of urban ozone (O3) in Shandong Province, a region with both land and sea environments in eastern China. The main research methods included the multiscale geographically weighted regression (MGWR) model and wavelet analysis. From 2016 to 2019, the O3 concentration increased year by year in most cities, but in 2020, the O3 concentration in all cities decreased. O3 concentration exhibited obvious regional differences, with higher levels in inland areas and lower levels in eastern coastal areas. The MGWR analysis results indicated the relationship between PD, urbanization rate (UR), and O3 was greater in coastal cities than that in the inland cities. Furthermore, the wavelet coherence (WTC) analysis results indicated that the daily maximum temperature was the most important factor influencing the O3 concentration. Compared with NO, NO2, and NOx (NOx ≡ NO + NO2), the ratio of NO2/NO was more coherent with O3. In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM2.5) exerted a greater impact on O3 in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O3 differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O3 pollution control in coastal and inland cities.

Discrepancies in ozone levels and temporal variations between urban and rural North China Plain

Effective emission reductions of some primary pollutants have brought down aerosol loadings but led to increasing relative importance of secondary pollutants, as was indicated by the rising O3 levels during warm seasons within urban and suburban areas of China, which has received much attention in recent years, especially in the North China Plain (NCP). This has raised serious concerns on its agricultural impacts, which were mainly evaluated based upon O3 model simulations or urban/suburban measurements due to a lack in long-term rural observations. In this study, we present highly valuable continuous O3 observations at a rural NCP site during 2013–2019. Compared to nearby urban/suburban sites, which experienced increased O3 levels, rural observations exhibited decreasing O3 mole fractions. While O3 mole fractions and AOT40 widely increased at urban/suburban NCP sites from 2013 to 2019, O3 observations in the rural NCP site (GC) revealed decreases, especially during summer and autumn with greater rates for AOT40. A reassessment of O3 agricultural impacts in the NCP region was performed using rural observations, resulting in wheat, maize and soybean averaged relative yield losses of 37 ± 14, 8 ± 4 and 30 ± 13% yr–1, respectively. O3 impacts on crop yields and resulting economic losses did not increase as was suggested by previous estimations based on urban/suburban O3 data. Our analyses indicated high overestimations (i.e., average relative differences in estimated crop production loss reaching 53%, 112% and 75%, respectively, for wheat, maize, and soybean). Despite alleviated O3 agricultural impacts, the total economic cost loss in Hebei province still took up 0.89% of the gross domestic production (3.47 × 1012 USD) in Hebei province. Since the China National Environmental Monitoring Center mainly aims at monitoring O3 levels in populated areas, observation sites representative of agricultural regions are lacking across China. The current study highlights the urgent necessity for the establishment of rural O3 observation networks and encourages extensive field experiments on exposure–response relationships of different crops varieties to O3 for more accurate agricultural impact evaluations. Additionally, explorations into the underlying mechanisms behind the reversed O3 temporal variation between rural and urban areas should be conducted for future development of pollution control strategies.

The association of ambient temperature with depression in middle-aged and elderly people: a multicenter prospective repeat survey study in China

Depression is the most common mental illness and contributes to a huge disease burden. However, few studies have examined the association between ambient temperature on depression. In this study, a three times repeated survey was conducted in 24 communities nationwide in China, through a face-to-face interview. Weather and air pollution data were collected from the European Centre for Medium-Range Weather Forecasts and the China National Environmental Monitoring Center, respectively. Depression was diagnosed by the 9-item Patient Health Questionnaire and generalized estimation equation models were used to examine the effects of ambient temperature on depression. Finally, 3811 individuals participated in the baseline survey, and a total of 9814 visits were completed during the three repeated survey periods. The relationship between ambient temperature and depression was linear. After adjusting for potential confounders, we observed that every 5 °C reduction in the two-week moving average temperature was associated with a 15.6% increase in depression (odds ratio (OR) = 1.156, 95% confidence interval (CI): 1.009–1.324, P= 0.038). Subgroup analyses showed that people aged ⩾65 years (OR = 1.269, 95% CI: 1.082–1.489, P< 0.01) were more vulnerable than those aged <65 years (OR = 0.873, 95% CI: 0.703–1.084, P= 0.22), while women (OR = 1.250, 95% CI: 1.054–1.483, P < 0.01) were more vulnerable than men (OR = 0.947, 95% CI: 0.771–1.162, P = 0.68). Results of the present study support an association between lower temperatures and increased risk of depression.

Gestational PM2.5 exposure may increase the risk of small for gestational age through maternal blood pressure and hemoglobin: A mediation analysis based on a prospective cohort in China, 2014–2018

BackgroundMaternal gestational PM2.5 exposure was associated with small for gestational age (SGA). Identifying potential mediating factors may help design preventive strategies to reduce this risk. ObjectiveThis study aimed to explore the roles of maternal blood pressure and hemoglobin may play in the PM2.5 exposure and SGA relationship among 117,162 births in 16 counties across China during 2014–2018. MethodsDaily PM2.5 concentration was collected from China National Environmental Monitoring Center. According to maternal residency during pregnancy, the PM2.5 exposure for each trimester and the whole pregnancy was assessed using an inverse-distance weighting approach. Repeated measurements of maternal blood pressure and hemoglobin during pregnancy were collected for each woman. We estimated the total effect of gestational PM2.5 exposure on SGA, and further tested the mediation effects of maternal blood pressure and hemoglobin concentration during pregnancy. ResultsOf 117,162 included mother-infant pairs, 11,361 (9.7 %) were SGA. The odds ratios of SGA associated with PM2.5 exposure (per 10 μg/m3 increase) in the second trimester and the whole pregnancy were 1.023 (95 % CI: 1.009, 1.037) and 1.024 (1.001, 1.048), respectively. We identified the independent mediating effect of blood pressure and hemoglobin in the second and third trimesters, with the proportion of mediation ranging from 1.64 % to 5.78 % and 2.40 % to 8.70 %, respectively. When considering the mediators jointly, we found a stronger mediating effect with a proportion of mediation ranging from 3.93 % to 13.69 %. DiscussionIncreases in maternal blood pressure and hemoglobin in the second and third trimesters can independently and jointly mediate the effects of gestational PM2.5 exposure on SGA. Monitoring and managing maternal blood pressure and hemoglobin during prenatal care may constitute a promising avenue to reducing SGA risk associated with gestational PM2.5 exposure.

Exposure to Ambient Air Pollutant PM10 in the Second Trimester of Pregnancy Is Associated with Preterm Birth: A Birth-Based Health Information Cohort Study.

Objectives We evaluated the effects of exposure to high concentrations of particulate matter (PM)10 on preterm birth (PTB) and identified a critical concentration of PM10 that could lead to PTB via a birth-based health information cohort study. Methods We conducted a birth-based cohort study consisting of nonanomalous singleton births at 22-42 weeks. PTB was defined as babies born alive before 37 weeks of pregnancy. Pregnancy period exposure averages were estimated for PM10 based on the China National Environmental Monitoring Centre (CNEMC). Pregnant women who lived within 50 km of the monitor station were recruited into this study. Logistic regression analyses were performed to determine the association between PTB and exposure to PM10 at different pregnancy periods with adjustment for confounding factors. Results The relative frequency of PTB was 8.7% in the study cohort of 5,291 singleton live births. A total of 1137 women had a high level of PM10 exposure (≥60 μg/m3) in the second trimester of pregnancy. The average concentrations of PM10 in the first, second, and third trimesters of pregnancy and throughout pregnancy were 53.8 μg/m3, 54.2 μg/m3, 55.6 μg/m3, and 54.3 μg/m3, respectively. The generalized additive model (GAM) analysis showed that there was a nonlinear correlation between PM10 and PTB in the second trimester of pregnancy (P < 0.001). The adjusted odds ratio between PTB and low concentration PM10 exposure (PM10 < 60 μg/m3) in the second trimester of pregnancy was 1.01 (95% CI 0.95-1.05). However, high PM10 exposure (PM10 ≥ 60 μg/m3) in the second trimester of pregnancy had an increased PTB risk even after adjustment for coexisting risk factors with an adjusted odds ratio of 1.78 (95% CI 1.69-1.87), and the incidence of PTB increased with an increase in PM10 exposure. Conclusions Our research discovered that exposure to high levels of PM10 increases the risk of PTB and the second trimester is the most vulnerable gestational period to ambient air pollution exposure. PM10 concentrations more than 60 μg/m3 are detrimental to pregnant women in their second trimester. This study has implications for health informatics-oriented healthcare decision support systems.