Chemical Characteristics of Water-Soluble Ions in Particulate Matter in Three Metropolitan Areas in the North China Plain

PM_2.5 and PM₁₀ samples were collected simultaneously in each season in Beijing, Tianjin and Shijiazhuang to identify the characteristics of water-soluble ion compositions in the North China Plain. The water-soluble ions displayed significant seasonal variation. The dominant ions were NO₃ ⁻, SO₄ ²⁻, NH₄ ⁺ and Cl⁻, accounting for more than 90% and 86% to the mass of total water-soluble ions in PM_2.5 and PM₁₀, respectively. The anion/cation ratio indicated that the ion acidity of each city varied both between sites and seasonally. Over 50% of the ion species were enriched in small particles ≤1 µm in diameter. The [NO₃ ⁻]/[SO₄ ²⁻] ratio indicated that vehicles accounted for the majority of the particulate pollution in Beijing. Shijiazhuang, a city highly reliant on coal combustion, had a higher SO₄ ²⁻ concentration.     

广州大夫山雨季林内外空气TSP和PM2.5浓度及水溶性离子特征

采用平行同步采样法,于2012年雨季,对广州市大夫山森林公园林内外空气的总悬浮颗粒物(TSP)和细颗粒物(PM_2.5)样品进行了24 h收集,测定了TSP和PM_2.5的质量浓度并分析了样品中水溶性无机离子成分。结果表明:林内外PM_2.5的质量浓度平均值分别为(40.18±10.47)和(55.79±13.01) g/cm³;林内外TSP的质量浓度分别为(101.32 ± 33.19)和(116.61±35.36) g/cm³。林内与林外比,PM_2.5和TSP平均质量浓度都显著减少(P < 0.05),表明森林能显著改善空气环境质量。TSP和PM_2.5中SO₄^2-、Na⁺、NH₄⁺和NO₃^-为水溶性无机离子主要成分,占总离子质量的80%以上,林外这些离子的浓度高于林内(NH₄⁺除外)。这4种离子雨季在空气中的主要存在方式为NaCl、Na₂SO₄、NH₄HSO₄和NH₄NO₃。计算表明,采样期间海盐对大夫山空气TSP和PM_2.5的水溶性组分中Na⁺和Cl^-贡献最大,其它元素主要源自陆地源。林内外TSP和PM_2.5的c(NO₃^-)/c(SO₄^2-)比值在0.3以下,表明固定源是大夫山森林公园空气主要污染贡献者,TSP中c(NO₃^-)/c(SO₄^2-)的比值大于PM_2.5的比值,说明移动源对TSP的贡献大于PM_2.5。     

The impact of outdoor air pollutants on outpatient visits for respiratory diseases during 2012–2016 in Jinan,China

Background

Few studies have investigated the associations between outdoor air pollution and outpatient visits for respiratory diseases (RDs) in general population.

Methods

We collected daily outpatient data of primary RDs from five hospitals in Jinan during January 2012 and December 2016, as well as daily measurements of air pollutants from the Jinan Environmental Monitoring Center and daily meteorological variables from the China Meteorological Data Sharing Service System. A generalized additive model (GAM) with quasi-Poisson regression was constructed to estimate the associations between daily average concentrations of outdoor air pollutants (PM_2.5,PM₁₀, SO₂, NO₂, CO and O₃) and daily outpatient visits of RDs after adjusting for long-time trends, seasonality, the “day of the week” effect, and weather conditions. Subgroup analysis stratified by gender, age group and the type of RDs was conducted.

Results

A total of 1,373,658 outpatient visits for RDs were identified. Increases of 10?μg/m³ in PM_2.5, PM₁₀, NO₂, CO and O₃ were associated with0.168% (95% CI, 0.072–0.265%), 0.149% (95% CI, 0.082–0.215%), 0.527% (95% CI, 0.211–0.843%), 0.013% (95% CI, 0.003–0.023%), and 0.189% (95% CI, 0.032–0.347%) increases in daily outpatient visits for RDs, respectively. PM_2.5 and PM₁₀ showed instant and continuous effects, while NO₂, CO and O₃ showed delayed effects on outpatient visits for RDs. In stratification analysis, PM_2.5 and PM₁₀ were associated with acute RDs only.

Conclusions

Exposure to outdoor air pollutants including PM_2.5, PM₁₀, NO₂, CO and O₃ associated with increased risk of outpatient visits for RDs.

     

Fine Particulate Air Pollution and Hospital Emergency Room Visits for Respiratory Disease in Urban Areas in Beijing,China, in 2013

BackgroundHeavy fine particulate matter (PM_2.5) air pollution occurs frequently in China. However, epidemiological research on the association between short-term exposure to PM_2.5 pollution and respiratory disease morbidity is still limited. This study aimed to explore the association between PM_2.5 pollution and hospital emergency room visits (ERV) for total and cause-specific respiratory diseases in urban areas in Beijing.MethodsDaily counts of respiratory ERV from Jan 1 to Dec 31, 2013, were obtained from ten general hospitals located in urban areas in Beijing. Concurrently, data on PM_2.5 were collected from the Beijing Environmental Protection Bureau, including 17 ambient air quality monitoring stations. A generalized-additive model was used to explore the respiratory effects of PM_2.5, after controlling for confounding variables. Subgroup analyses were also conducted by age and gender.ResultsA total of 92,464 respiratory emergency visits were recorded during the study period. The mean daily PM_2.5 concentration was 102.1±73.6 μg/m³. Every 10 μg/m³ increase in PM_2.5 concentration at lag₀ was associated with an increase in ERV, as follows: 0.23% for total respiratory disease (95% confidence interval [CI]: 0.11%-0.34%), 0.19% for upper respiratory tract infection (URTI) (95%CI: 0.04%-0.35%), 0.34% for lower respiratory tract infection (LRTI) (95%CI: 0.14%-0.53%) and 1.46% for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) (95%CI: 0.13%-2.79%). The strongest association was identified between AECOPD and PM_2.5 concentration at lag_0-3 (3.15%, 95%CI: 1.39%-4.91%). The estimated effects were robust after adjusting for SO₂, O₃, CO and NO₂. Females and people 60 years of age and older demonstrated a higher risk of respiratory disease after PM_2.5 exposure.ConclusionPM_2.5 was significantly associated with respiratory ERV, particularly for URTI, LRTI and AECOPD in Beijing. The susceptibility to PM_2.5 pollution varied by gender and age.     

Chang impact analysis of level 3 COVID-19 alert on air pollution indicators using artificial neural network

In this study, mean monthly and diurnal variations in fine particulate matters (PM_2.5), nitrate, sulfate, and gaseous precursors were investigated during the Level 3 COVID-19 alert from May 19 to July 27 in 2021. For comparison, the historical data during the identical period in 2019 and 2020 were also provided to determine the effect of the Level 3 COVID-19 alert on aerosols and gaseous pollutants concentrations in Taichung City. A machine learning model using the artificial neural network technique coupled with a kinetic model was applied to predict NO_x, O₃, nitrate (NO₃⁻), and sulfate (SO₄²⁻) to investigate potential emission sources and chemical reaction mechanism. D during the Level 3 COVID-19 alert, a decrease in NO_x concentration due to a decrease in traffic flow under the NO_x-saturated regime was observed to enhance the secondary NO₃⁻ and O₃ formation. The present models were shown to predict 80.1, 77.0, 72.6, and 67.2% concentrations of NO_x, O₃, NO₃⁻, and SO₄²⁻, respectively, which could help decision-makers for pollutant emissions reduction policies development and air pollution control strategies. It is recommended that more long-term datasets, including water soluble inorganic salts (WIS), precursors including OH radicals, NH₃, HNO₃, and H₂SO₄, be provided by regulatory air quality monitoring stations to further improve the prediction model accuracy.     

The Novel Relationship between Urban Air Pollution and Epilepsy: A Time Series Study

MethodsA hospital record-based study was carried out in Xi’an, a heavily-polluted metropolis in China. Daily baseline data were obtained. Time-series Poisson regression models were applied to analyze the association between air pollution and epilepsy.ResultsA 10 μg/m³ increase of NO₂, SO₂, and O₃ concentrations corresponded to 3.17% (95%Cl: 1.41%, 4.93%), 3.55% (95%Cl: 1.93%, 5.18%), and -0.84% (95%Cl: -1.58%, 0.09%) increase in outpatient-visits for epilepsy on the concurrent days, which were significantly influenced by sex and age. The effects of NO₂ and SO₂ would be stronger when adjusted for PM_2.5. As for O₃, a -1.14% (95%Cl: -1.90%, -0.39%) decrease was evidenced when adjusted for NO₂. The lag models showed that the most significant effects were evidenced on concurrent days.ConclusionsWe discovered previously undocumented relationships between short-term air pollution exposure and epilepsy: while NO₂ and SO₂ were positively associated with outpatient-visits of epilepsy, O₃ might be associated with reduced risk.     

Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

Objective

Ambient fine particulate matter (PM_2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM_2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM_2.5 mass concentrations for urban residences in Beijing.

Methods

In this study, 24-h real-time indoor and ambient PM_2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM_2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM_2.5 mass concentration.

Results

Hourly ambient PM_2.5 mass concentrations were 3–280 μg/m³ with a median of 58 μg/m³, and hourly indoor counterpart were 4–193 μg/m³ with a median of 34 μg/m³. The median indoor/ambient ratio of PM_2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM_2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM_2.5 mass concentrations on the community basis (coefficients: r≥0.90, p<0.0001), and the ambient data explained ≥84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM_2.5 mass concentrations.

Conclusions

PM_2.5 of ambient origin made dominant contribution to residential indoor PM_2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM_2.5 raised the concern of exposure misclassification when using ambient PM_2.5 mass concentrations as exposure surrogates. PM_2.5 of indoor origin still had minor influence on indoor PM_2.5 mass concentrations, particularly at 11:00–13:00 and 22:00–0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM_2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models.     

Estimation of Short-Term Effects of Air Pollution on Stroke Hospital Admissions in Wuhan,China

Background and Objective

High concentrations of air pollutants have been linked to increased incidence of stroke in North America and Europe but not yet assessed in mainland China. The aim of this study is to evaluate the association between stroke hospitalization and short-term elevation of air pollutants in Wuhan, China.

Methods

Daily mean NO₂, SO₂ and PM₁₀ levels, temperature and humidity were obtained from 2006 through 2008. Data on stroke hospitalizations (ICD 10: I60–I69) at four hospitals in Wuhan were obtained for the same period. A time-stratified case-crossover design was performed by season (April-September and October-March) to assess effects of pollutants on stroke hospital admissions.

Results

Pollution levels were higher in October-March with averages of 136.1 µg/m³ for PM₁₀, 63.6 µg/m³ for NO₂ and 71.0 µg/m³ for SO₂ than in April-September when averages were 102.0 µg/m³, 41.7 µg/m³ and 41.7 µg/m³, respectively (p<.001). During the cold season, every 10 µg/m³ increase in NO₂ was associated with a 2.9% (95%C.I. 1.2%–4.6%) increase in stroke admissions on the same day. Every 10 ug/m³ increase in PM₁₀ daily concentration was significantly associated with an approximate 1% (95% C.I. 0.1%–1.4%) increase in stroke hospitalization. A two-pollutant model indicated that NO₂ was associated with stroke admissions when controlling for PM₁₀. During the warm season, no significant associations were noted for any of the pollutants.

Conclusions

Exposure to NO₂ is significantly associated with stroke hospitalizations during the cold season in Wuhan, China when pollution levels are 50% greater than in the warm season. Larger and multi-center studies in Chinese cities are warranted to validate our findings.     

Study on the Traffic Air Pollution inside and outside a Road Tunnel in Shanghai,China

To investigate the vehicle induced air pollution situations both inside and outside the tunnel, the field measurement of the pollutants concentrations and its diurnal variations was performed inside and outside the Xiangyin tunnel in Shanghai from 13:00 on April 24th to 13:00 on April 25th, 2013. The highest hourly average concentrations of pollutants were quantified that CO, NO, NO₂ and NO_X inside the tunnel were 13.223 mg/m³, 1.829 mg/m³, 0.291 mg/m³ and 3.029 mg/m³, respectively, while the lowest ones were 3.086 mg/m³, 0.344 mg/m³, 0.080 mg/m³ and 0.619 mg/m³. Moreover, the concentrations of pollutants were higher during the daytime, and lower at night, which is relevant to the traffic conditions inside the tunnel. Pollutants concentrations inside the tunnel were much higher than those outside the tunnel. Then in a case of slow wind, the effect of wind is much smaller than the impact of pollution sources. Additionally, the PM_2.5 concentrations climbed to the peak sharply (468.45 µg/m³) during the morning rush hours. The concentrations of organic carbon (OC) and elemental carbon (EC) in PM_2.5 inside the tunnel were 37.09–99.06 µg/m³ and 22.69–137.99 µg/m³, respectively. Besides, the OC/EC ratio ranged from 0.72 to 2.19 with an average value of 1.34. Compared with the results of other tunnel experiments in Guangzhou and Shenzhen, China, it could be inferred that the proportion of HDVs through the Xiangyin tunnel is relatively lower.     

Promoted Relationship of Cardiovascular Morbidity with Air Pollutants in a Typical Chinese Urban Area

BackgroundA large number of studies about effects of air pollutants on cardiovascular mortality have been conducted; however, those investigating association between air pollutants and cardiovascular morbidity are limited, especially in developing countries.MethodsA time-series analysis on the short-term association between outdoor air pollutants including particulate matter (PM) with diameters of 10 µm or less (PM₁₀), sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) and cardiovascular morbidity was conducted in Tianjin, China based on 4 years of daily data (2008–2011). The morbidity data were stratified by sex and age. The effects of air pollutants during the warm season and the cool season were also analyzed separately.ResultsEach increase in PM₁₀, SO₂, and NO₂ by increments of 10 µg/m³ in a 2-day average concentration was associated with increases in the cardiovascular morbidity of 0.19% with 95 percent confidence interval (95% CI) of 0.08–0.31, 0.43% with 95% CI of 0.03–0.84, and 0.52% with 95% CI of −0.09–1.13, respectively. The effects of air pollutants were more evident in the cool season than those in the warm season, females and the elderly were more vulnerable to outdoor air pollution.ConclusionsAll estimated coefficients of PM₁₀, SO₂ and NO₂ are positive but only the effect of SO₂ implied statistical significance at the 5% level. Moreover, season, sex and age might modify health effects of outdoor air pollutants. This work may bring inspirations for formulating local air pollutant standards and social policy regarding cardiovascular health of residents.     

Impact of novel coronavirus disease (COVID-19) lockdown on ambient air quality of Saudi Arabia

The outbreak of COVID-19 has spread globally affecting human activities but with improvement in ambient air quality. The first case of the virus in the Kingdom of Saudi Arabia was on the 2nd of March 2020. The impact of COVID-19 lockdown on the ambient air quality of the Kingdom of Saudi Arabia for the first time using data from nine cities was determined in this study. Hourly air quality data, based on concentrations of carbon monoxide (CO), particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and ozone (O₃), and meteorological conditions (atmospheric temperature, relative humidity, and wind speed) of the nine cities studied were obtained from Saudi Arabian General Authority of Meteorology and Environmental Protection (GAMEP), for the period between January 2019 to May 2020. Significant variation (p < 0.05) was recorded for the five atmospheric pollutants across the cities before and during the lockdown, with lower concentrations during the lockdown except for the concentration of O₃ in Tabuk, Al Qasim, and Haql. This can be a result of NO and O₃ reaction, causing the inability of effective O₃ depletion. The percentage changes in concentrations of CO (33.60%) and SO₂ (44.16%) were higher in Jeddah; PM₁₀ (91.12%) in Riyadh, while NO₂ (44.35%) and O₃ (18.98%) were highest in Makkah. However, even though there was a decrease in pollutants concentrations during the lockdown, the concentrations for CO, PM₁₀, SO₂, NO_2, and O₃ were still above WHO 24 h and annual mean limit levels. The COVID-19 lockdown in the Kingdom of Saudi Arabia revealed the possibility of significant atmospheric pollutant reduction by controlling traffic, activities by industries, and environmentally friendly transportation programs such as green commuting programs.     

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing,China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R ² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.     

Air Pollution in China: Mapping of Concentrations and Sources

China has recently made available hourly air pollution data from over 1500 sites, including airborne particulate matter (PM), SO₂, NO₂, and O₃. We apply Kriging interpolation to four months of data to derive pollution maps for eastern China. Consistent with prior findings, the greatest pollution occurs in the east, but significant levels are widespread across northern and central China and are not limited to major cities or geologic basins. Sources of pollution are widespread, but are particularly intense in a northeast corridor that extends from near Shanghai to north of Beijing. During our analysis period, 92% of the population of China experienced >120 hours of unhealthy air (US EPA standard), and 38% experienced average concentrations that were unhealthy. China’s population-weighted average exposure to PM_2.5 was 52 μg/m³. The observed air pollution is calculated to contribute to 1.6 million deaths/year in China [0.7–2.2 million deaths/year at 95% confidence], roughly 17% of all deaths in China.     

Longitudinal Relationship between Personal CO and Personal PM2.5 among Women Cooking with Woodfired Cookstoves in Guatemala

Household air pollution (HAP) due to solid fuel use is a major public health threat in low-income countries. Most health effects are thought to be related to exposure to the fine particulate matter (PM) component of HAP, but it is currently impractical to measure personal exposure to PM in large studies. Carbon monoxide (CO) has been shown in cross-sectional analyses to be a reliable surrogate for particles<2.5 µm in diameter (PM_2.5) in kitchens where wood-burning cookfires are a dominant source, but it is unknown whether a similar PM_2.5-CO relationship exists for personal exposures longitudinally. We repeatedly measured (216 measures, 116 women) 24-hour personal PM_2.5 (median [IQR] = 0.11 [0.05, 0.21] mg/m³) and CO (median [IQR] = 1.18 [0.50, 2.37] mg/m³) among women cooking over open woodfires or chimney woodstoves in Guatemala. Pollution measures were natural-log transformed for analyses. In linear mixed effects models with random subject intercepts, we found that personal CO explained 78% of between-subject variance in personal PM_2.5. We did not see a difference in slope by stove type. This work provides evidence that in settings where there is a dominant source of biomass combustion, repeated measures of personal CO can be used as a reliable surrogate for an individual''s PM_2.5 exposure. This finding has important implications for the feasibility of reliably estimating long-term (months to years) PM_2.5 exposure in large-scale epidemiological and intervention studies of HAP.     

Polybrominated Diphenyl Ethers (PBDEs) in PM2.5, PM10, TSP and Gas Phase in Office Environment in Shanghai,China: Occurrence and Human Exposure

To evaluate risk via inhalation exposure of polybrominated diphenyl ethers (PBDEs) in office environment, thirty-six pairs air samples including PM_2.5 (particles with aerodynamic diameter less than 2.5 μm), PM₁₀ (particles with aerodynamic diameter less than 10 μm), total suspended particles (TSP) with matching gas phase were collected in office environment in Shanghai, China. The average concentrations of PM_2.5, PM₁₀ and TSP were 20.4, 27.2 and 50.3 μg/m₃, respectively. Σ₁₅PBDEs mean concentrations in PM_2.5, PM₁₀, TSP and gas phase were 51.8, 110.7, 148 and 59.6 pg/m³, respectively. Much more PBDEs distributed in fine fractions than coarse ones. PBDEs congener profiles found in PM_2.5, PM₁₀ and TSP (dominated by BDE-209) were different from that in gas phase (dominated by the tri- to penta-BDEs). Approximately 3.20 pg/kg/d PM_2.5 bound PBDEs can be inhaled into the lung; 3.62 pg/kg/d PM₁₀-PM_2.5(particles with aerodynamic diameter of 2.5-10 μm) bound PBDEs tended to be deposited in the upper part of respiratory system, and the intake of PBDEs via gas-phase was 2.74 pg/kg/d. The exposure of PBDEs was far below the minimal risk levels (MRLs), indicating lower risk from PBDEs via inhalation in the studied office in Shanghai.     

基于环境库兹涅茨曲线的我国大气污染防治重点区域环境空气质量与经济增长关系研究

改革开放以来,中国经济迅猛发展,但大气污染等环境问题日益突出。进入21世纪,我国通过颁布实施多项大气污染防治政策,将京津冀及周边地区、长三角地区、珠三角地区等大气污染较严重的区域划定为重点区域,针对性制定治污措施和实施减排工程,努力推动区域环境空气质量改善。基于2000-2019年我国31个省（自治区、直辖市）（以下简称31个省份）GDP,以及SO₂、PM₁₀、NO₂三项大气污染物浓度数据,利用环境库兹涅茨曲线（EKC,Environmental Kuznets Curve）模型,对31个省份和京津冀及周边地区、长三角地区、珠三角地区的经济增长情况、大气污染物浓度演变以及二者之间的关系进行了系统全面的分析评估。研究结果显示：（1）近年来实施的各项大气污染防治政策,特别是2013年以来颁布实施的《大气污染防治行动计划》《打赢蓝天保卫战三年行动计划》,推动环境空气质量改善的同时,促进了经济发展与环境保护长期关系协调性逐步增强,除NO₂浓度呈U型外,31个省份SO₂浓度、PM₁₀浓度与人均GDP的EKC曲线呈倒U型和倒N型,并处于快速下降阶段。（2）京津冀及周边地区SO₂浓度与人均GDP呈倒U型,且处于快速下降阶段;PM₁₀和NO₂浓度均呈现U型关系,且均处于上升期。（3）长三角地区SO₂、PM₁₀浓度与人均GDP呈现倒U型和U型,但均处于下降阶段;NO₂浓度与人均GDP无相关关系。（4）珠三角地区SO₂、PM₁₀和NO₂浓度与人均GDP均呈现倒U型关系,且均处于下降阶段。为此,建议"十四五"期间我国政府要继续实施新一轮的大气污染防治行动计划,聚焦机动车NO_x污染管控,大力推动NO₂浓度稳步下降,以实现我国环境空气质量持续改善,为统筹经济高质量发展和生态环境高水平保护奠定坚实基础。     

Association between Air Pollutants and Asthma Emergency Room Visits and Hospital Admissions in Time Series Studies: A Systematic Review and Meta-Analysis

Background

Air pollution constitutes a significant stimulus of asthma exacerbations; however, the impacts of exposure to major air pollutants on asthma-related hospital admissions and emergency room visits (ERVs) have not been fully determined.

Objective

We sought to quantify the associations between short-term exposure to air pollutants [ozone (O₃), carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and particulate matter ≤10μm (PM₁₀) and PM_2.5] and the asthma-related emergency room visits (ERV) and hospitalizations.

Methods

Systematic computerized searches without language limitation were performed. Pooled relative risks (RRs) and 95% confidence intervals (95%CIs) were estimated using the random-effect models. Sensitivity analyses and subgroup analyses were also performed.

Results

After screening of 246 studies, 87 were included in our analyses. Air pollutants were associated with significantly increased risks of asthma ERVs and hospitalizations [O₃: RR(95%CI), 1.009 (1.006, 1.011); I² = 87.8%, population-attributable fraction (PAF) (95%CI): 0.8 (0.6, 1.1); CO: RR(95%CI), 1.045 (1.029, 1.061); I² = 85.7%, PAF (95%CI): 4.3 (2.8, 5.7); NO₂: RR(95%CI), 1.018 (1.014, 1.022); I² = 87.6%, PAF (95%CI): 1.8 (1.4, 2.2); SO₂: RR(95%CI), 1.011 (1.007, 1.015); I² = 77.1%, PAF (95%CI): 1.1 (0.7, 1.5); PM₁₀: RR(95%CI), 1.010 (1.008, 1.013); I² = 69.1%, PAF (95%CI): 1.1 (0.8, 1.3); PM_2.5: RR(95%CI), 1.023 (1.015, 1.031); I² = 82.8%, PAF (95%CI): 2.3 (1.5, 3.1)]. Sensitivity analyses yielded compatible findings as compared with the overall analyses without publication bias. Stronger associations were found in hospitalized males, children and elderly patients in warm seasons with lag of 2 days or greater.

Conclusion

Short-term exposures to air pollutants account for increased risks of asthma-related ERVs and hospitalizations that constitute a considerable healthcare utilization and socioeconomic burden.     

川渝地区空气质量时空分布格局及影响因素

川渝地区尤其是四川盆地已成为我国空气污染最严重的地区之一,基于2018—2019年川渝地区128个城市站和71个县级站空气质量监测及自然与社会经济数据,采用全局和局部莫兰指数分析了川渝地区空气质量指数(AQI)和不同空气质量分指数(IAQI)的时空格局,并采用偏最小二乘回归(PLSR)从较为宏观的尺度综合分析了川渝地区空气污染的主要驱动因素。研究结果表明：(1)川渝地区空气质量整体为良,主要污染物为O₃,其次为PM₁₀和PM_2.5。盆地区与高原区的主要污染物分别为PM_2.5和O₃;(2)AQI及PM_2.5、PM₁₀、NO₂呈“U”型变化,春冬季最高,夏秋季最低;O₃则在内部两区域都大致呈倒“U”型变化,但峰值分布时间与持续时长明显不同;SO₂和CO年内无明显变化;(3)各污染物具有明显的空间聚集性特征,AQI及PM₁₀、PM_2.5     

Study of PM10, PM2.5, and PM1 levels in during dust storms and local air pollution events in urban and rural sites in Tehran

The aim of this study is to survey the PM₁₀, PM_2.5, and PM₁ concentrations in rural and urban areas in Tehran province during cold, warm and dust storm days from December 22, 2016 to June 5, 2017 using Grimm Model aerosol spectrometer. During the study period, daily PM₁₀, PM_2.5, and PM₁ concentrations ranged from 27.2 to 244.96, 8.4 to 77.9, and 6.5 to 56.8 μg/m³ in urban sites, and 22.8 to 286.4, 6 to 41.1, and 2.1 to 20.2 μg/m³ in rural parts, respectively. Particularly, both daily WHO limits for outdoor PM₁₀ (50.0 μg/m³) and PM_2.5 (25.0 μg/m³) exceeded in 95% and 83% of the outdoor measurements in winter and 82% and 58% in total sampled days in urban site, respectively. The 24-h average PM₁₀ and PM_2.5 concentrations also exceeded by 59% and 18% in winter and by 36% and 14% of all sampling days in rural site, respectively. During the dust storm, the 24-h average PM₁₀, PM_2.5, and PM₁ concentrations were, respectively 4.7, 2, and 1.96 times higher than those in urban site and 2, 1.7, and 1.3 times more than those in rural site in all sampled days.     

Ambient Air Pollution Associated with Suppressed Serologic Responses to Pneumocystis jirovecii in a Prospective Cohort of HIV-Infected Patients with Pneumocystis Pneumonia

Background

Ambient air pollution (AAP) may be associated with increased risk for Pneumocystis pneumonia (PCP). The mechanisms underlying this association remain uncertain.

Objectives

To determine if real-life exposures to AAP are associated with suppressed IgM antibody responses to P. jirovecii in HIV-infected (HIV+) patients with active PCP, and to determine if AAP, mediated by suppressed serologic responses to Pneumocystis, is associated with adverse clinical outcomes.

Methods

We conducted a prospective cohort study in HIV+ patients residing in San Francisco and admitted to San Francisco General Hospital with microscopically confirmed PCP. Our AAP predictors were ambient air concentrations of particulate matter of < 10 µm in diameter (PM₁₀) and < 2.5 µm in diameter (PM_2.5), nitrogen dioxide (NO₂), ozone (O₃), and sulfur dioxide (SO₂) measured immediately prior to hospital admission and 2 weeks prior to admission. Our primary outcomes were the IgM serologic responses to four recombinant P. jirovecii major surface glycoprotein (Msg) constructs: MsgC1, MsgC3, MsgC8, and MsgC9.

Results

Elevated PM₁₀ and NO₂ exposures immediately prior to and two weeks prior to hospital admission were associated with decreased IgM antibody responses to P. jirovecii Msg. For exposures immediately prior to admission, every 10 µg/m³ increase in PM₁₀ was associated with a 25 to 35% decrease in IgM responses to Msg (statistically significant for all the Msg constructs), and every 10 ppb increase in NO₂ was associated with a 19-45% decrease in IgM responses to Msg (statistically significant for MsgC8 and MsgC9). Similar findings were seen with exposures two weeks prior to admission, but for fewer of the Msg constructs.

Conclusions

Real life exposures to PM₁₀ and NO₂ were associated with suppressed IgM responses to P. jirovecii Msg in HIV+ patients admitted with PCP, suggesting a mechanism of immunotoxicity by which AAP increases host susceptibility to pulmonary infection.