Concern over the health effects of fine particles in the ambient environment led the U.S. Environmental Protection Agency to develop the first standard for PM2.5 （particulate matter less than 2.5 μm） ...in 1997. The Particle Technology Laboratory at the University of Minnesota has helped to establish the PM2.5 standard by developing many instruments and samplers to perform atmospheric measurements. In this paper, we review various aspects of PM2.5, including its measurement, source apportionment, visibility and health effects, and mitigation. We focus on PM2.s studies in China and where appropriate, compare them with those obtained in the U.S. Based on accurate PM2.5 sampling, chemical analysis, and source apportionment models, the major PM2.5 sources in China have been identified to be coal combustion, motor vehicle emissions, and industrial sources. Atmospheric visibility has been found to correlate well with PM2.s concentration. Sulfate, ammonium, and nitrate carried by PM2.s, commonly found in coal burning and vehicle emissions, are the dominant contributors to regional haze in China. Short-term exposure to PM2.s is strongly associated with the increased risk of morbidity and mortality from cardiovascular and respiratory diseases in China. The strategy for PMzs mitigation must be based on reducing the pollutants from the two primary sources of coal-fired power plants and vehicle emissions. Although conventional Particulate Emission Control Devices （PECD） such as electrostatic precipitators in Chinese coal-fired power plants are generally effective for large particles, most of them may not have high collection efficiency of PM2.5. Baghouse filtration is gradually incorporated into the PECD to increase the PM2.5 collection efficiency. By adopting stringent vehicle emissions standard such as Euro 5 and 6, the emissions from vehicles can be gradually reduced over the years. An integrative approach, from collaboration among academia, government, and industries, can effectively manage and mitigate the PM2.s pollution in China.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The main objectives of this study were (1) investigation of the temporal variations of ambient fine particulate matter (PM2.5) and ground level ozone (O3) concentrations in Tehran megacity, the ...capital and most populous city in Iran, over a 10-year period from 2006 to 2015, and (2) estimation of their long-term health effects including all-cause and cause-specific mortality. For the first goal, the data of PM2.5 and O3 concentrations, measured at 21 regulatory monitoring network stations in Tehran, were obtained and the temporal trends were investigated. The health impact assessment of PM2.5 and O3 was performed using the World Health Organization (WHO) AirQ+ software updated in 2016 by WHO European Centre for Environment and Health. Local baseline incidences in Tehran level were used to better reveal the health effects associated with PM2.5 and O3. Our study showed that over 2006–2015, annual mean concentrations of PM2.5 and O3 varied from 24.7 to 38.8 μg m−3 and 35.4 to 76.0 μg m−3, respectively, and were significantly declining in the recent 6 years (2010–2015) for PM2.5 and 8 years (2008–2015) for O3. However, Tehran citizens were exposed to concentrations of annual PM2.5 exceeding the WHO air quality guideline (WHO AQG) (10 μg m−3), U.S. EPA and Iranian standard levels (12 μg m−3) during entire study period. We estimated that long-term exposure to ambient PM2.5 contributed to between 24.5% and 36.2% of mortality from cerebrovascular disease (stroke), 19.8% and 24.1% from ischemic heart disease (IHD), 13.6% and 19.2% from lung cancer (LC), 10.7% and 15.3% from chronic obstructive pulmonary disease (COPD), 15.0% and 25.2% from acute lower respiratory infection (ALRI), and 7.6% and 11.3% from all-cause annual mortality in the time period. We further estimated that deaths from IHD accounted for most of mortality attributable to long-term exposure to PM2.5. The years of life lost (YLL) attributable to PM2.5 was estimated to vary from 67,970 to 106,706 during the study period. In addition, long-term exposure to O3 was estimated to be responsible for 0.9% to 2.3% of mortality from respiratory diseases. Overall, long-term exposure to ambient PM2.5 and O3 contributed substantially to mortality in Tehran megacity. Air pollution is a modifiable risk factor. Appropriate sustainable control policies are recommended to protect public health.
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•Long-term trends and health impacts of PM2.5 and O3 in Tehran were evaluated from 2006–2015.•Tehran citizens were exposed to annual PM2.5 approximately 2 to 4 times higher than the WHO guideline level at all times.•Annual mean O3 concentrations declined significantly over the whole period study.•In 2015, approximately 3800 deaths (> 10 per day) were attributable to long-term exposure to ambient PM2.5 in Tehran.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
To improve air quality, China formulated the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013. In the present study, the changes in the concentration of air pollutants after the ...implementation of APPCAP were investigated based on nationwide monitoring data. From the results, it is evident that the annual mean concentrations of PM2.5, PM10, SO2, and CO show a significant downward trend over 2015–2018, with decreasing rates of 3.4, 4.1, 3.8, and 70 μg m−3/year, respectively. However, no significant change was found in NO2 while maximum daily 8 h average O3 concentration (MDA8 O3) was increased by 3.4 μg m−3/year during the four years. Spatially, the highest decrease in PM2.5 was found in Beijing-Tianjin-Hebei (BTH), followed by central China and northeast China, while the Pearl River Delta (PRD), Yungui Plateau, and northwest China showed less decreases. MDA8 O3 had a higher increase in BTH, central China, Yangtze River Delta (YRD), and PRD. With the decrease in PM2.5 in recent years, cumulative population exposure to PM2.5 gradually decreased, whereas there was still more than 65% of the population exposing to annual PM2.5 higher than the standard of 35 μg m−3 in 2018. In contrast, the health effects of O3 gradually increased with 13.1%, 14.3%, 20.4%, and 21.7% of the population exposed to unhealthy O3 levels in summer from 2015 to 2018. O3 pollution is causing severe health risks with estimated nationwide mortality of 70,024 (95% CI: 55,510–84,501), 79,159 (95% CI: 62,750–95,525), 105,150 (95% CI: 83,378–126,852), and 104,404 (95% CI: 82,784–125,956) in the four years, respectively. This clearly shows that the target of air pollution control in China shifts and coordinated control of PM2.5 and O3 is urgently needed after the successful implementation of APPCAP.
•Four years of air quality monitoring data across China were analyzed.•PM2.5, PM10, SO2, and CO showed a significant decrease in recent years.•O3 was increased by 3.4 μg m−3/year during the four-years.•Severe O3 pollution is posing a threat to human health in China.•The coordinated control of PM2.5 and O3 must be urgently implemented.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Delhi is one of the most polluted cities worldwide and a comprehensive understanding and deeper insight into the air pollution and its sources is of high importance. We report 5 months of highly ...time-resolved measurements of non-refractory PM2.5 and black carbon (BC). Additionally, source apportionment based on positive matrix factorization (PMF) of the organic aerosol (OA) fraction is presented. The highest pollution levels are observed during winter in December/January. During that time, also uniquely high chloride concentrations are measured, which are sometimes even the most dominant NR-species in the morning hours. With increasing temperature, the total PM2.5 concentration decreases steadily, whereas the chloride concentrations decrease sharply. The concentrations measured in May are roughly 6 times lower than in December/January. PMF analysis resolves two primary factors, namely hydrocarbon-like (traffic-related) OA (HOA) and solid fuel combustion OA (SFC-OA), and one or two secondary factors depending on the season. The uncertainties of the PMF analysis are assessed by combining the random a-value approach and the bootstrap resampling technique of the PMF input. The uncertainties for the resolved factors range from ±18% to ±19% for HOA, ±7% to ±19% for SFC-OA and ±6 % to ±11% for the OOAs. The average correlation of HOA with equivalent black carbon from traffic (eBCtr) is R2 = 0.40, while SFC-OA has a correlation of R2 = 0.78 with equivalent black carbon from solid fuel combustion (eBCsf). Anthracene (m/z 178) and pyrene (m/z 202) (PAHs) are mostly explained by SFC-OA and follow its diurnal trend (R2 = 0.98 and R2 = 0.97). The secondary oxygenated aerosols are dominant during daytime. The average contribution during the afternoon hours (1 pm–5 pm) is 59% to the total OA mass, with contributions up to 96% in May. In contrast, the primary sources are more important during nighttime: the mean nightly contribution (22 pm–3 am) to the total OA mass is 48%, with contributions up to 88% during some episodes in April.
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•Over 65% of the daily PM2.5 concentrations exceed the national air quality standard.•Exceptionally high chloride contribution during early mornings in the cold period•Significant solid fuel combustion contribution throughout the full campaign•PMF uncertainty assessment
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The COVID-19 epidemic broke out in Wuhan, Hubei in December 2019 and in January 2020 and was later transmitted to the entire country. Quarantine measures during Chinese New Year effectively ...alleviated the spread of the epidemic, but they simultaneously resulted in a decline in anthropogenic emissions from industry, transportation, and import and export of goods. Herein, we present the major chemical composition of non-refractory PM2.5 (NR-PM2.5) and the concentrations of gaseous pollutants in an urban site in Shanghai before and during the quarantine period of the COVID-19 epidemic, which was Jan. 8―23 and Jan. 24―Feb. 8, respectively. The observed results show that the reduction in PM2.5 can be mainly attributed to decreasing concentrations of nitrate and primary aerosols. Nitrate accounted for 37% of NR-PM2.5 before the quarantine period when there was no emission reduction. During the quarantine period, the nitrate concentration decreased by approximately 60%, which is attributed to a reduction in the NOx concentration. Ammonium, as the main balancing cation, showed an approximately 45% simultaneous decrease in concentration. The concentrations of chloride and hydrocarbon-like organic aerosols from primary emissions also declined due to limited human activities. By contrast, sulphate and oxygenated organic aerosols showed a slight decrease in concentration, with their contributions increasing to 27% and 18%, respectively, during the quarantine period, which resulted in two pollution episodes with PM2.5 exceeding 100 μg/m3. This study provides a better understanding of the impact of quarantine measures on variations of the PM2.5 concentration and chemical compositions. Atmospheric oxidation capacities based on the oxidant (Ox = O3 + NO2) and oxidation ratios have been discussed for elucidating the source and formation of haze in an environment with lower anthropogenic emissions. With increasing contribution of secondary aerosols, lower NOx and nitrate concentrations did not completely avoid haze in Shanghai during the epidemic.
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•Quarantine measures led to a reduction in the concentrations of PM2.5, SO2, NOx, and CO in Shanghai.•Reduction in NOx led to increasing O3 and decreasing nitrate.•Reduction in PM2.5 is attributed to the decreasing concentrations of primary aerosols and nitrate.•The increasing contribution of sulphate and OOA inhibited further PM2.5 reduction.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this study, hourly and daily records since 2005 and correlation, regression and composite methods were used to analyze the long-term evolution of surface O3 and PM2.5 concentrations at the rural ...station of Shangdianzi (SDZ) and urban station of Baolian (BL) over Beijing and their relationships with meteorological conditions. The results show that the mean concentrations of PM2.5 (O3) decreased (increased) at the urban and rural stations over the last decade. The linear trends of the annual mean concentrations of PM2.5 at BL and SDZ were −31.8 ug/m3/10yr (−4.3%/yr) (p < 0.01) and −13.3 ug/m3/10yr (−2.9%/yr) (p < 0.05), respectively. In winter, the mean wind speed (Ws) and relative humidity (RH) were the most closely correlated with O3 at both stations, whereas RH and sunshine hours (S) were most closely correlated with PM2.5. The correlation coefficients and explained variances in spring and autumn were generally less than those in winter and greater than those in summer. Moreover, increase in precipitation can significantly reduce the PM2.5 concentration in both urban and rural areas in Beijing, whereas trace and light precipitation more effectively decreases the O3 concentration. Concentrations of PM2.5 (O3) on haze days increased by 114% (3%) and 162% (20%) compared with that on non-haze days at the urban and rural stations, respectively. This result suggests that haze is a major manifestation of air pollution in Beijing.
•PM2.5 (O3) concentrations decreased (increased) in Beijing over the last decade.•Meteorological factors play important role in the daily variability of pollutants.•Hazy days are a major manifestation of air pollution in Beijing.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Long-term exposure to ambient and household particulate matter (PM2.5) causes death and health loss, and both are the leading risk factor to global disease burden. We assessed spatiotemporal trends ...of ambient and household PM2.5 attributable burdens across various diseases at the global, regional, and national levels from 1990 to 2017.
Data on PM2.5-attributable disease burdens were extracted from the Global Burden of Disease (GBD) study 2017. Numbers and age-standardized rates (ASRs) of deaths, disability-adjusted life years (DALYs) and corresponding estimated annual percentage change (EAPC) were estimated by disease, age, sex, Socio-demographic Index (SDI), locations.
Exposure to PM2.5 contributed to 4.58 million deaths and 142.52 million DALYs globally in 2017, among which ambient PM2.5 contributed to 64.2% deaths and 58.3% DALYs. ASRs of deaths and DALYs in 2017 decreased to 59.62/105 persons with an EAPC of −2.15 (95% CI: 2.21 to −2.09) and 1856.61/105 persons with an EAPC of −2.58 (95% CI: 2.64 to −2.51), respectively compared to those in 1990. Ambient PM2.5-attributable Non-communicable diseases (NCDs) have dominated major concern in middle and low SDI countries especially in South Asia and East Asia, while household PM2.5-attributable lower respiratory infections (LRIs) still caused the largest burden in low SDI countries in Africa and Asia. Those under 5 and over 70 years old had the largest burdens in PM2.5 attributable LRI and NCDs, respectively.
In conclusion, ambient PM2.5-attributable NCDs have threatened public health in middle and low SDI countries, while household PM2.5-attributable LRI still caused the largest burden in low SDI countries. More positive strategies should be tailored to reduce PM2.5-attributable burdens considering specific settings globally.
•PM2.5-attributed disease burdens transitioned from LRI to NCDs, with the greatest burden in regions with lower SDI.•Although ASR of death and DALY decreased, overall PM2.5-attributed disease burdens remain heavy.•Increasing ambient PM2.5-attributed non-communicable diseases primarily imperiled the health of older people.•Decreasing household PM2.5-attributed lower respiratory infection still dominated in children under 5 in low SDI regions.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Fine particulate matter (PM2.5) pollution in Eastern China (EC) has raised concerns due to its adverse effects on air quality, climate, and human health. This study investigated the long-term ...variation trend in satellite-derived PM2.5 concentrations and how it was related to pollutant emissions and meteorological parameters over EC and seven regions of interest (ROIs) during 1998–2016. Over EC, the annual mean PM2.5 increased before 2006 due to the enhanced emissions of primary PM2.5, NOx and SO2, but decreased with the reduced SO2 emissions after 2006 evidently in response to China's clean air policies. In addition, results from statistical analyses indicated that in the North China Plain (NCP), Northeast China (NEC), Sichuan Basin (SCB) and Central China (CC) planetary boundary layer height (PBLH) was the dominant meteorological driver for the PM2.5 decadal changes, and in the Pearl River Delta (PRD) wind speed is the leading factor. Overall, the variation in meteorological parameters accounted for 48% of the variances in PM2.5 concentrations over EC. The population-weighted PM2.5 over EC increased from 36.4 μg/m3 in 1998–2004 (P1) to 49.4 μg/m3 in 2005–2010 (P2) then decreased to 46.5 μg/m3 in 2011–2016 (P3). In the NCP and NEC, the percentages of the population living above the World Health Organization (WHO) Interim Target-1 (IT-1, 35 μg/m3) have risen steadily over the past 20 yr, reaching maxima of 97.3% and 78.8% in P3, respectively, but decreases of ∼30% from P2 to P3 were found for the SCB and PRD.
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•The joint effect of emission and meteorological determined the decadal trend of PM2.5•The changes in meteorological parameters explained 48% of the variances in PM2.5.•Planetary boundary layer height was the dominant driver for the decadal changes of PM2.5•Eastern China has experienced slight decreases in the population-weighted mean PM2.5 over the past 10 year.
The joint effect of emissions and meteorological determined the decadal trend in PM2.5. The decadal variation in meteorological parameters accounted for 48% of the variances in PM2.5 concentrations over Eastern China. Eastern China has experienced slight decreases in the population-weighted mean PM2.5 over the past 10 year.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Evidence concerning the effects of different chemical components of particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on asthma is limited, and the methodology to compare the ...relative importance of different PM2.5 components is lacking.
Our aim was to examine the associations between PM2.5 components and asthma and investigate which constituent of PM2.5 possessed the most harmful effect on asthma.
A total of 45,690 subjects in 6 countries were surveyed from 2007 to 2010. We geocoded the residential community addresses of the participants and used satellite remote sensing and chemical transport modeling to estimate their annual average concentrations of PM2.5 constituents. Mixed-effects generalized additive models were utilized to examine the associations between PM2.5 constituents and prevalence of asthma. We further used counterfactual analyses to determine the potential number of asthma cases.
We identified 6178 patients with asthma among the participants, producing an asthma prevalence of 13.5%. The odds ratio for asthma associated with per-SD increment was 1.12 for PM2.5 mass, 1.12 for organic carbon, 1.18 for black carbon, 1.19 for sulfate, 1.28 for ammonium, and 1.21 for nitrate after controlling for potential confounders. Our counterfactual analyses suggested that ammonium was responsible for a substantial decline in asthma cases (by 1382 cases, corresponding to 22.37% of overall cases) if the concentration was reduced to the 5th percentile of the current level.
Our study suggests that some chemical components of PM2.5 (including black carbon, organic carbon, sulfate, ammonium, and nitrate) might be hazardous constituents contributing to the prevalence of asthma; among them, ammonium might be responsible for a substantial proportion of asthma cases if reduced to a certain level.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this study, PM2.5 airborne particulate matter was collected over a full year at a costal site of the Central Mediterranean Sea and analysed for its chemical composition and oxidative potential ...(OP), determined by the dithiothreitol (DTT) and the ascorbic acid (AA) assays. In autumn-winter, the volume normalized oxidative OP (OPV) were 0.29 ± 0.03 nmol min−1 m−3 and 0.21 ± 0.03 nmol min−1 m−3 for the DTT (OPDTTV) and AA (OPAAV) assay, respectively. In spring-summer the OPDTTV values were higher than OPAAV responses, i.e., 0.19 ± 0.02 nmol min−1 m−3 vs. 0.09 ± 0.01 nmol min−1 m−3. Overall, marked seasonality was observed with higher values in Autumn-Winter (AW) than in Spring-Summer (SS), i.e., 1.5 and 2.3 times increase for OPDTTV and OPAAV, respectively.
In the cold season, the OPV activity was broadly correlated with metals and carbon species, such as K+, NO3−, Ba, Cd, Cu, Fe, Mn, P, V, OC, EC, Acetate, Oxalate and Glycolate (p < 0.05). This suggested the main contribution of a “mixed anthropogenic” source, consisting of the biomass burning (K+, OC and EC) and traffic (Ba, Cu, Fe, Mn, V, EC) emissions. In SS, OPV was significantly correlated with only few species i.e., OC, EC, Cu, and NO3−, suggesting main association with the “mixed anthropogenic” and the “reacted dust” sources.
For each sampling day, PM2.5 and PM10 samples were simultaneously collected and analysed to investigate the variation of the OP activity in relation with the particle size and chemical composition.
OPDTTV values exhibited a poor particle-size dependence, with similar values close to 0.20 ± 0.04 nmol min−1 m−3 in both fractions. This could be explained by the association of OPDTTV with species mainly accumulated in the fine fraction, i.e., OC, POC and EC and K+. Otherwise, the OPAAV responses exhibited a clear particle-size dependence, with significantly higher values for PM10 than for PM2.5, i.e., 0.35 ± 0.06 vs. 0.21 ± 0.03 nmol min−1 m−3 in AW and 0.23 ± 0.04 vs. 0.09 ± 0.01 in SS. This may be supported by the strong correlation of OPAAV with Cu and Fe, which were most abundant metals in the PM10 fraction.
The data of specific monitoring days were investigated in detail to better highlight the impact of some individual redox active species on the OPDTTV and OPAAV responses.
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•Oxidative potential was assessed for PM2.5 at a Central Mediterranean Site.•Oxidative potential and chemical composition of PM2.5 and PM10 were compared.•The dependence of the OPDTT and OPAA responses on seasons were investigated.•OPDTT were similar in PM2.5 and PM10 and highly associated with OC, EC and K+.•OPAA were higher in PM10 than in PM2.5 and highly associated with Cu and Fe.
The oxidative potential of PM2.5 and PM10 samples was assessed with Dithiothreitol and Ascorbic Acid assays: the variation of OP responses was related with the PM size and chemical composition.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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