Fine Particulate Pollution Research Articles

Particle number size distributions and formation and growth rates of different new particle formation types of a megacity in China

To understand the contribution of new particle formation (NPF) events to ambient fine particle pollution, measurements of particle size distributions, trace gases and meteorological conditions, were conducted at a suburban site (NJU) from October to December 2016 and at an industrial site (NUIST) from September to November 2015 in Nanjing. According to the temporal evolution of the particle size distributions, three types NPF events were observed: typical NPF (Type A), moderate NPF events (Type B) and strong NPF (Type C) events. The favorable conditions for Type A events included low relative humidity, low concentration of pre-existing particles, and high solar radiation. The favorable conditions of Type B events were similar to Type A, except for a higher concentration of pre-existing particles. Type C events were more likely to happen with the higher relative humidity, lower solar radiation and continuous growth of pre-existing particle concentration. The formation rate of 3 nm (J3) was the lowest for Type A events and highest for Type C events. In contrast, the growth rates of 10 nm and 40 nm particles were the highest for Type A, and lowest for Type C. Results show that NPF events with only higher J3 would lead to the accumulation of nucleation mode particles. Sulfuric acid was important for the formation of particles but had little effect on the growth of particle size.

Assessing drivers of coordinated control of ozone and fine particulate pollution: Evidence from Yangtze River Delta in China

Previous studies have focused on a certain atmospheric pollutant, and few studies that comprehensively considered the drivers to synergistic impact on multiple pollutants. This study uses panel data of 41 cities in the Yangtze River Delta Urban Agglomeration (YRDUA) from 2005 to 2018. We aim to assess drivers of coordinated control for fine particulate (PM2.5) and ozone (O3) pollution using atmospheric remote sensing and spatial econometric model. Satellite image extraction shows that the key areas of pollution control are concentrated in the eastern coastal areas and northern cities. Here we show the empirical results of the Spatial Durbin Model indicating the drivers that significantly coordinated control of PM2.5 and O3 pollution: economic growth, urbanization, population density and energy intensity. The promotion of urbanization of YRDUA can help mitigate pollution, which proves that the new urbanization approach can improve environmental quality. Other significant drivers have their own adverse effects on PM2.5 and O3 pollution. Besides, the spillover effects of drivers are stronger than their local effects, which means that regional joint prevention and control will significantly improve the ambient air quality. As a result, policy recommendations are finally put forward such as promoting new-type urbanization, further standardizing the regional joint prevention and control mechanism, and exploring source management of PM2.5 and O3 pollution.

Assessment of PM2.5 exposure risk towards SDG indicator 11.6.2 – A case study in Beijing

• Spatiotemporal PM 2.5 exposure risk in Beijing was analyzed. • Progress of SDG 11.6.2 has been evaluated at the city level. • A localized framework was designed for the assessment of progress towards SDG 11.6.2. • Provided experience and demonstration for similar city-level assessments in the future. The SDG Target 11.6 was committed to "reduce the adverse per capita environmental impact of cities", one of its indicators 11.6.2 mainly focusing on air quality and used to measure the health impacts of fine particulate pollution on urban populations. However, given that this indicator was designed for the assessment and monitoring at national, regional, and global levels, and few studies to quantitively evaluate it at the city-level currently, whether it can be directly applied to the city-level and fully reflects the intensity of the exposure risk of fine particulate pollution is still unknown. In light of this problem, taking Beijing as an example, we use methods such as population-weighted PM 2.5 concentrations, trend analysis, and geographic spatial distribution measurement to analyze the PM 2.5 exposure risk in Beijing from the perspective of multiscale spatiotemporal characteristics of PM 2.5 concentrations and exposure risk intensity, finally realized a localized assessment framework towards SDG 11.6.2 to quantitatively evaluate the progress of Beijing. The results not only clarified the sustainable development status of air quality in Beijing but also provided experience and demonstration for the similar city-level monitoring and assessment towards SDG 11.6.2 in the future.

Ambient fine particulate pollution hysteresis triggers wake-up stroke and rapidly triggers non-wake-up stroke: a case-crossover study.

Atmospheric pollutants increase the risk of acute ischemic stroke (AIS) which has been widely reported. However, little is known about the relationships between air pollution and specific subsets of AIS, such as wake-up stroke (WUS) and non-wake-up stroke (non-WUS). This study aimed to explore the relationship between WUS and non-WUS and atmospheric pollutants. A total of 1432 patients (331 WUS patients and 1101 non-WUS patients) were admitted to a tertiary hospital from 2016 to 2019. A time-stratified case-crossover design and a conditional logistic regression model to study the associations of change in pollutant concentration with WUS and non-WUS events were constructed. Data analysis revealed that WUS-related risks increased 48 to 72h after the increase in the PM2.5 concentration (each 10μg/m3 increase, lag 0-72h) [threshold OR (95% CI):18μg/m3 1.03 (0.94-1.11), 35μg/m3 1.01 (0.92-1.12), 50μg/m3 1.04 (0.91-1.19)]; the non-WUS-related risk increased 1 to 6h after the increase in the PM2.5 concentration (each 10μg/m3 increase, lag 0-1h) [threshold OR (95% CI):18μg/m3 1.01 (0.98-1.03), 35μg/m3 1.00 (0.97-1.04), 50μg/m3 1.01 (0.96-1.05)] (lag 0-6h) [threshold OR (95% CI): 18μg/m3 1.00 (0.97-1.03), 35μg/m3 1.00 (0.97-1.04), 50μg/m3 1.01 (0.97-1.06)]; O3 exposure was related to WUS events, and its impact on WUS events was stronger and longer-lasting (1-96h) than its impact on non-WUS events (1-6h). Greater than or equal to 65years of age, overweight (BMI ≥ 25), and diabetes had a significantly greater risk of WUS associated with increased PM2.5 concentration in the previous 12-96h than patients without these conditions. Patients with hypertension and smoking had a significant risk of non-WUS associated with increased PM2.5 concentration in the previous 1-6h. The increase in PM2.5 concentration in the cold season increased the risk of both WUS and non-WUS events. Ambient air pollution hysteresis triggers WUS and rapidly triggers non-WUS, even if the degree of pollutant is relatively low. Patients with elderly, overweight, and diabetes appeared particularly susceptible to WUS, and patients with hypertension and smoking history were susceptible to non-WUS. We need to expand the sample for further investigation into mechanisms by which environmental pollutants trigger WUS or non-WUS.

RETRACTED: PM2.5, Household Income, and Health Hazard: The Role of Economic Integration in the Process of Decarbonization in the Developing Economies

The goal of this study is to examine the impact of household income and air pollution on the health of developing-country residents. The panel dataset of twelve developing nations used for this purpose. High levels of fine particulate matter in the air are linked to increased health problems, and lower incomes for households in the economies studied. However, effective environmental management and renewable energy resources have a significant role in controlling the harmful impact of fine particulate matter in the air. It highlights that developing economies could lower the fine particulate matter in the air by strengthening the regional environmental policies and adopting renewable resources. In emerging countries, environmentally friendly strategies and the shift from carbon base to non-carbon-based energy would minimize pollution in the atmosphere and improve the quality of life for inhabitants and other organisms. Improved quality of life and lower levels of fine particulate matter pollution are expected to increase people’s per capita income in the region. Finally, air pollution is a transboundary phenomenon; therefore, strict compliance with environmental protection policies at the regional level is a prerequisite for improved quality of the natural environment.

Sleep disturbance exacerbates the cardiac conduction abnormalities induced by persistent heavy ambient fine particulate matter pollution: A multi-center cross-sectional study

Fine particulate matter (PM2.5) exposure and sleep disturbance have been significantly associated with adverse cardiovascular outcomes, however, the combined effects of these two factors are still unclear. We conducted a multi-center cross-sectional study from November 2018 to May 2019 in the Beijing–Tianjin–Hebei region in China to investigate the potential modifying effects of sleep disturbance on associations between cardiac conduction abnormalities and PM2.5 exposure, as well as the combined effects of sleep disturbance and heavy pollution episodes, which were defined based on the PM2.5 mass concentration (≥75 μg/m3, falling in the 75th/90th percentile) and duration (1 day and ≥2 days). The sleep quality and sleep duration of all participants were evaluated using the Pittsburgh Sleep Quality Index. Standard 12-lead electrocardiogram (ECG) test was performed to measure the heart rate (HR), QRS duration (time taken for ventricular depolarization), HR corrected QT interval (time for ventricular depolarization and repolarization) and PR interval (time for atrioventricular conduction). Multivariable linear regression models were performed to evaluate the associations of PM2.5 and heavy pollution events on ECG parameters and the joint effects with sleep disturbance. We found PM2.5 exposure was independently associated with prolonged QRS and QTc intervals. Association between PM2.5 and the QTc interval was significantly stronger in participants with poor sleep quality. For each 10-μg/m3 increase in PM2.5 concentration, the QTc interval in the participants with poor sleep quality increased by 0.41 % (95 % confidence interval: 0.19, 0.64). In addition, heavy PM2.5 pollution episodes, especially extremely heavy pollution of long duration, were found to have synergistic effects with sleep disturbance on ECG parameters. Our findings provide evidence that PM2.5 exposure, especially heavy pollution episodes, may increase abnormal cardiac conduction and have a synergistic effect with sleep disturbance. Improving sleep hygiene is crucial to protect the heart health of the general population.

Progressively narrow the gap of PM2.5 pollution characteristics at urban and suburban sites in a megacity of Sichuan Basin, China

Nowadays, the fine particle pollution is still severe in some megacities of China, especially in the Sichuan Basin, southwestern China. In order to understand the causes, sources, and impacts of fine particles, we collected PM2.5 samples and analyzed their chemical composition in typical months from July 2018 to May 2019 at an urban and a suburban (background) site of Chengdu, a megacity in this region. The daily average concentrations of PM2.5 ranged from 5.6-102.3 µg/m3 and 4.3-110.4 µg/m3 at each site. Secondary inorganics and organic matters were the major components in PM2.5 at both sites. The proportion of nitrate in PM2.5 has exceeded sulfate and become the primary inorganic component. SO2 was easier to transform into sulfate in urban areas because of Mn-catalytic heterogeneous reactions. In contrast, NO2 was easily converted in suburbs with high aerosol water content. Furthermore, organic carbon in urban was much greater than that in rural, other than elemental carbon. Element Cr and As were the key cancer risk drivers. The main sources of PM2.5 in urban and suburban areas were all secondary aerosols (42.9%, 32.1%), combustion (16.0%, 25.2%) and vehicle emission (15.2%, 19.2%). From clean period to pollution period, the contributions from combustion and secondary aerosols increased markedly. In addition to tightening vehicle controls, urban areas need to restrict emissions from steel smelters, and suburbs need to minimize coal and biomass combustion in autumn and winter.

Tripling of western US particulate pollution from wildfires in a warming climate

SignificanceRecord-setting fires in the western United States over the last decade caused severe air pollution, loss of human life, and property damage. Enhanced drought and increased biomass in a warmer climate may fuel larger and more frequent wildfires in the coming decades. Applying an empirical statistical model to fires projected by Earth System Models including climate-ecosystem-socioeconomic interactions, we show that fine particulate pollution over the US Pacific Northwest could double to triple during late summer to fall by the late 21st century under intermediate- and low-mitigation scenarios. The historic fires and resulting pollution extremes of 2017-2020 could occur every 3 to 5 y under 21st-century climate change, posing challenges for air quality management and threatening public health.

Prediction Tool on Fine Particle Pollutants and Air Quality for Environmental Engineering.

This article focuses on the research, design and implementation of a prediction tool for air quality to estimate pollutant concentrations, contributing to environmental engineering. It addresses prediction of fine particle air pollutants of diameter less than 2.5 µm (particulate matter 2.5), their concentration being substantially influenced by urban traffic. We collect worldwide multicity data from health-related public sources on which mining is performed using classical data mining/machine learning paradigms: association rules, clustering and classification. Challenges include adapting appropriate techniques based on data, and capturing subtle domain-specific aspects. The prediction tool is built using knowledge discovered by mining, leveraging health standards, catering to novice, intermediate and expert users. The prediction output is accurate, efficient, interpretable and useful as evident from our experiments. The tool is helpful for urban decision support. This work is beneficial in developing software systems such as intelligent tutors, mobile device apps and smart city tools. It contributes to smart environment, mobility and living, making a positive impact on smart cities and sustainability. In this work, we claim that classical computational paradigms in their fundamental form can be adapted to solve environmental engineering problems, with easy comprehension, as per the Occam’s razor principle that advocates simplicity. This article constitutes applied research: using computational techniques to solve domain-specific problems. Future work includes exploring models in deep learning such as CNN and Bi-LSTM, and considering different types of pollutants as well as other sources besides multicity traffic data, to conduct further studies. This would address additional challenges with enhancements.

Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong-Hong Kong-Macau Greater Bay Area of China Using a Regional-To-Local Coupling Model.

Ultrahigh‐resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5) concentrations over the past decade has triggered ozone (O3) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh‐resolution perspective. We propose a regional‐to‐local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC‐limited O3 formation regime, and traffic is a key factor in controlling NOx and O3. The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 μg/m³, and the maximum increase in the median daily maximum 8‐hr rolling O3 is >10 μg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 μg/m³. The daily averaged PM2.5 decreases by <2 μg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O3 episode analysis of the dual‐control scenario leads to O3 decreases of up to 15 μg/m³ (8‐hr metric) and 25 μg/m³ (1‐hr metric) in rural areas.

Fine particulate matter pollution characteristics and source apportionment of Changchun atmosphere.

In order to study the pollution characteristics and main sources of fine particulate matter in the atmosphere of the city of Changchun, PM2.5 samples were collected during the four seasons in 2014, and representative months for each season are January, April, July, and October. Sample collection was carried out on 10 auto-monitoring stations in Changchun, and PM2.5 mass concentration and its chemical components (including inorganic elements, organic carbon, elemental carbon, and water-soluble ions) were measured. The results show that the annual average mass concentration of PM2.5 in Changchun in 2014 was about 66.77μg/m3. Organic matter was the highest component in PM2.5, followed by secondary inorganic ions (SNA), mineral dust (MIN), elemental carbon (EC), and trace elements (TE). Positive matrix factorization (PMF) results gave seven factors, namely, industrial, biomass and coal burning, industrial and soil dust, motor vehicle, soil and secondary ion, light industrial, and hybrid automotive and industrial sources in PM2.5, with contributing values of 18.9%, 24.2%, 5.7%, 23.0%, 11.5%, 13.0%, and 3.6%, respectively.

Real-time Source Apportionment of PM2.5 and Potential Geographic Origins of Each Source During Winter in Wuhan

China has always suffered from serious atmospheric fine particle (PM2.5) pollution in winter, and PM2.5 in Wuhan is particularly affected by regional transportation. Based on the hourly monitoring dataset of chemical components during the winter period, this study identified the real-time sources of PM2.5 in Wuhan using a positive matrix factorization (PMF) model. A cluster analysis of backward trajectories and the concentration weighted trajectory were applied to obtain the potential source regions and transportation routes. During the observation period, ρ(PM2.5) was (75.1±29.2) μg·m-3, and there were two pollution episodes, one of which was mainly affected by the air masses coming from the northwest direction. In the first pollution episode, the increasing concentration of water-soluble ions was the main reason for the high PM2.5 value, and the concentrations of NH4+, NO3-, and SO42- were 1.6, 1.7, and 2.1 times those during the cleaning period, respectively. The other episode was affected by the air masses coming from the east direction, and the secondary organic components were clearly formed. Secondary inorganic aerosol contributed the most (34.1%) to PM2.5, followed by vehicular exhaust (23.7%), coal combustion (11.5%), road dust (10.9%), iron- and steel-producing processes (8.7%), and firework displays (5.7%). Biomass burning contributed the least (5.3%). Our examination of the diurnal variation revealed that the maximum contribution of iron- and steel-producing processes appeared at 08:00[(17.5±18.8) μg·m-3], and the lowest was at 01:00[(10.4±10.9) μg·m-3], which stayed high in the daytime and low at night. The contribution of vehicular exhaust showed a double peak at 09:00[(42.1±24.8) μg·m-3] and 20:00[(41.6±19.5) μg·m-3]. In the first pollution period, the contribution rate of secondary inorganic aerosol increased significantly, indicating that the long-distance transport under the northwest air mass promoted the generation of secondary components. In the second pollution period, the contribution rates of vehicular exhaust, coal combustion, iron- and steel-producing processes, and road dust increased, mainly located in the local area, the northwest of Jiangxi and the south of Anhui province. This reflected the influence of industrial processes, road transportation, and dust contribution along the Yangtze River on PM2.5. Biomass burning had a relatively high contribution for air masses from the northern regions, including Henan, Anhui, the south of Hebei, and the southwest of Shanxi provinces. The regional transport of pollutants from biomass combustion in the North China Plain during the winter would have an impact on Wuhan. This study can provide scientific and technological support for identifying the causes of atmospheric haze pollution in Wuhan during the winter and for the joint prevention and control of atmospheric particulate matter.

Towards air quality particulate-matter monitoring using low-cost sensor data and visual exploration techniques: case study of Kisumu, Kenya

Air quality monitoring in developing countries is in deplorable condition despite its impact on many aspects of life such as population health. Among the very fine particulate pollutants in the air, PM2.5 and PM10 are more numerous and therefore more dangerous. Higher exposure to these fine particles, which are difficult to perceive by the eye, would contribute to an increased risk of cardiovascular and respiratory diseases, as well as lung cancers. Low-cost sensor-based technologies are now emerging as an effective alternative to monitoring the concentration of particulate matter in ambient air. This technology also has the advantage of being less complex and therefore can involve more citizen participation. A concrete example on the African continent is the initiative of the Sensor.Africa project is based on the involvement and commitment of citizens to collect and share this data for free in their cities. Among more than 25 cities on the continent where the project has already been launched is the city of Kisumu in Kenya where it has been implemented since February 2019. The process used to deploy and process the data from the low-cost sensors was explained in detail for better understanding. The deployment of these sensors can open up a plethora of opportunities, but it also rises a number of challenges for effective air quality monitoring. In our case, the data obtained after sensor calibration sometimes suffer from a lack of accuracy and outliers. Therefore, data visualisation techniques are used to solve this problem before analysing and proposing perspectives for further use by different stakeholders. From a health point of view, few records showed critical values in this city for the PM2.5 and PM10 indicators.

Recommendations of Controlling and Preventing Acute Health Risks of Fine Particulate Matter Pollution - China, 2021.

The task force has comprehensively reviewed efforts for air pollution prevention and control, the acute health effects of fine particles (PM2.5), and the health benefits of air pollution prevention and control in China. It has been found that the overall prevention and control of ambient PM2.5 pollution in China has made remarkable progress in recent years. However, it still remains at a relatively high level. Short-term exposure to ambient PM2.5 significantly increases the mortality and morbidity risk of Chinese residents, resulting in changes to levels of relevant biological markers. Prolonged PM2.5 heavily polluted weather greatly increases the risk of cardiovascular disease morbidity and mortality. Among chemical composition of PM2.5, carbon-containing components, some inorganic salts, and heavy metals are linked with the health impacts. The health risks of PM2.5 pollution are higher for children, the elderly, and patients with cardiovascular or respiratory diseases than for the general population because the former groups are vulnerable subpopulations. The implementation of air pollution prevention and control policies has significantly improved human health. The implementation of personal protective equipment can significantly reduce the health damage caused by short-term exposure to ambient PM2.5 pollution. Based on scientific evidence of PM2.5 pollution and acute health risks in China, the following three recommendations are proposed. 1) The policy recommendations for the prevention and control of ambient PM2.5 pollution include the following: to continuously strengthen the widespread use and efficient development of clean energy; to further promote industrial upgrading; to focus on the control of transportation pollution; to keep improving the modernization system of air pollution control; to formulate and refine relevant standards for air quality gradually; and to estimate the effects and health benefits after the implementation of clean air actions, and relevant policies. 2) Prevention of ambient PM2.5 pollution and protection of public health recommendations include the following: to strengthen the release of air pollution monitoring and relevant information; to strengthen awareness of air pollution hazards; to clarify the guidance and recommendations for protecting population health from air pollution; and to strengthen the health protection of population vulnerable to ambient air pollution. 3) Recommendations for research on health risks of air pollution include the following: to strengthen research on air pollutant monitoring technology and monitoring system based on the promotion of accurate exposure assessment; to systematically carry out full-spectrum identification and correlation studies of air pollutants and health effects; to conduct studies on key toxic components and early biomarker inventory of air pollution health effects; to discover the toxicity mechanisms of the key toxic components of air pollutants; to carry out research on population health risk assessment and early warning of combined exposure to air pollutants; and to execute comprehensive studies on the health and economic benefits of pollution and carbon reduction under the national strategies of carbon neutrality and beautiful China.

Fine Particulate Pollution Driven by Nitrogen Dioxide and Ozone in the Moisture Urban Atmospheric Environment in Pearl River Delta Region of South China

Fine Particulate Pollution Driven by Nitrogen Dioxide and Ozone in the Moisture Urban Atmospheric Environment in Pearl River Delta Region of South China

Fine Particulate Pollution Driven by Nitrate in the Moisture Urban Atmospheric Environment in Pearl River Delta Region of South China

Fine Particulate Pollution Driven by Nitrate in the Moisture Urban Atmospheric Environment in Pearl River Delta Region of South China

Chemical Composition Characteristics and Source Apportionment of PM2.5 in Ceramic Industrial Base during Winter

The national architectural ceramic industrial center in east China is suffering from serious ambient fine particle pollution. The study reported herein describes an effort to ascertain the degree and sources of the PM2.5 collected in a ceramic industrial base during winter. The major chemical components in PM2.5 were analyzed, including carbonaceous aerosols, water-soluble ions, and inorganic elements. The chemical mass balance (CMB) model, backward trajectory method and potential source contribution function model, etc. were used to track and identify possible sources and contributions in the formation of the PM2.5. The results showed that the average PM2.5 concentration during sampling period was 134 ± 74.7 µg m–3, which exceeding World Health Organization (WHO) Air Quality Guidelines levels. The dominant components in the PM2.5 at this sampling site were found to be secondary ions (sulfate and nitrate) and carbon fractions. Water-soluble ions and total carbon contributed about 48.7% and 13.9% of the PM2.5 mass, respectively. In addition, the SO42–/NO3– ratio in the ambient PM2.5 during the sampling period was 1.16, indicating that it was the result of primarily emissions from stationary sources. Furthermore, source apportionment using the CMB model indicated that a ceramic industry source was the main contributor to the PM2.5 mass, which accounted for about 27.9%, and this was followed by secondary formation dust sources, and gasoline/diesel vehicle exhaust emissions and motor vehicle non-exhaust emissions. Based on the backward trajectory analysis and potential source apportionment, it was found that PM2.5 regional transmission existed, but it originated primarily from local sources and surrounding areas. Hence, this study provided a scientific basis for identifying the sources of PM2.5 pollution during a typical pollution period and provided important input for PM2.5 control strategies in a typical industrial area.

Towards Multi-Scale Space-Time Characteristics of Air Quality and Population Exposure Risk

In order to formulate policies to control regional air pollution and promote sustainable human–land system development, it is crucial to study the space–time distribution of air pollution and the population exposure risk. Existing studies are limited to individual fine particulate pollutants, which does not fully reflect the comprehensiveness of air quality. In addition, the spatiotemporal distribution of air quality and population exposure risk at different scales need to be further quantified. In this study, we used air monitoring station data and population spatial distribution data to analyze the spatiotemporal characteristics of air quality, including seasonal variations, variations before and during heating periods, and the occurrence frequency of priority pollutants in the traditional industrial areas of Northeast China in 2015. The population exposure–air pollution risk (PE-APR) model was used to calculate the population exposure risk at different spatial scales. The results suggest that GIS methods and air monitoring data help to establish a comprehensive air quality analysis framework, revealing spring–summer differentiation and the change trend of air quality with latitude. There are significant clustering features of air quality. A grid-scale population exposure–air pollution risk map is not restricted by administrative boundaries, which helps to discover high-risk areas of the main regional economic corridors and differences between inner cities and suburbs. This study provides a reference for understanding the space–time evolution of regional air pollution and formulating coordinated cross-regional air pollution strategies.

Source apportionment and regional transport of PM2.5 during haze episodes in Beijing combined with multiple models

Atmospheric fine-particle (PM2.5) pollution is a prominent regional issue that is affected by local emissions, regional transport, and secondary formation and impacts human health, air quality, and climate. Identifying the origin and types of pollution sources that are transported to the receptor site is essential for the development of joint prevention and control measures. This study developed a combined method to explore the source-receptor relationship during haze episodes of the heating season in Beijing, by combining positive matrix factorization (PMF) model with Lagrangian particle model (FLEXPART-WRF) and chemical transport model (CAMx). Six source types identified by PMF with high-time-resolution online measurements were counted in different transport pathways including local, south, east, and north. The results showed that secondary source contributed the most to PM2.5, which was affected by regional transport of Baoding, Langfang, and Tangshan. Among major primary sources, vehicle source was concentrated locally. Coal combustion contributed a higher proportion locally (15.8%) and in the south (15.0%), and Baoding, Langfang, and Xingtai along the Taihang Mountains were predominant potential source regions. Biomass burning contributed a higher proportion in the south (19.0%) and northeast (22.6%), and adjacent southern Hebei and Northeastern areas were the predominant potential source regions. Moreover, the variations in PM2.5 sources, footprints, and source regions of two haze cases from pre-pollution to dissipation were analyzed. EP1, with a more southern transport, was caused by high secondary source and coal combustion, while EP2 was characterized by secondary source and biomass burning from Hebei and Liaoning Province transport. In particular, the emission distribution of surrounding cities along transport pathways had an important effect on PM2.5 sources in Beijing. This study demonstrated that the combined method can provide guidance for implementing effective emission mitigation measures and improving the regional air quality.

Secondary organic aerosol association with cardiorespiratory disease mortality in the United States

Fine particle pollution, PM2.5, is associated with increased risk of death from cardiorespiratory diseases. A multidecadal shift in the United States (U.S.) PM2.5 composition towards organic aerosol as well as advances in predictive algorithms for secondary organic aerosol (SOA) allows for novel examinations of the role of PM2.5 components on mortality. Here we show SOA is strongly associated with county-level cardiorespiratory death rates in the U.S. independent of the total PM2.5 mass association with the largest associations located in the southeastern U.S. Compared to PM2.5, county-level variability in SOA across the U.S. is associated with 3.5× greater per capita county-level cardiorespiratory mortality. On a per mass basis, SOA is associated with a 6.5× higher rate of mortality than PM2.5, and biogenic and anthropogenic carbon sources both play a role in the overall SOA association with mortality. Our results suggest reducing the health impacts of PM2.5 requires consideration of SOA.