Chemical speciation and source apportionment of fine particulate matter in Santiago, Chile, 2013

Local and NON-LOCAL source apportionment of black carbon and combustion generated PM2.5

Current methods for measuring black carbon aerosol (BC) by optical methods apportion BC to fossil fuel and wood combustion. However, these results are aggregated: local and non-local combustion sources are lumped together. The spatial apportioning of carbonaceous aerosol sources is challenging in remote or suburban areas because non-local sources may be significant. Air quality modeling would require highly accurate emission inventories and unbiased dispersion models to quantify such apportionment. We propose FUSTA (FUzzy SpatioTemporal Apportionment) methodology for analyzing aethalometer results for equivalent black carbon coming from fossil fuel (eBCff) and wood combustion (eBCwb). We applied this methodology to ambient measurements at three suburban sites around Santiago, Chile, in the winter season 2021. FUSTA results showed that local sources contributed ∼80% to eBCff and eBCwb in all sites. By using PM2.5 - eBCff and PM2.5 - eBCwb scatterplots for each fuzzy cluster (or source) found by FUSTA, the estimated lower edge lines showed distinctive slopes in each measurement site. These slopes were larger for non-local sources (aged aerosols) than for local ones (fresh emissions) and were used to apportion combustion PM2.5 in each site. In sites Colina, Melipilla and San Jose de Maipo, fossil fuel combustion contributions to PM2.5 were 26 % (15.9 μg m-3), 22 % (9.9 μg m-3), and 22 % (7.8 μg m-3), respectively. Wood burning contributions to PM2.5 were 22 % (13.4 μg m-3), 19 % (8.9 μg m-3) and 22% (7.3 μg m-3), respectively. This methodology generates a joint source apportionment of eBC and PM2.5, which is consistent with available chemical speciation data for PM2.5 in Santiago.

An overview of air pollution research in Chile: Bibliometric analysis and scoping review, challenger and future directions

This study provides a comprehensive overview and bibliometric analysis of air pollution research in Chile from 1980 to 2022. The analysis reveals a significant increase in scientific production, a 9.2 annual growth rate, and an H-index of 60. The research spans 33 countries and is influenced by environmental sciences, meteorology, and atmospheric sciences journals. The top ten authors account for 33.49 % of all publications, with local institutions contributing more than 35 %. The University of Chile and the Pontifical Catholic University of Chile are significant contributors. The most cited articles focus on health impacts and various pollutant sources, emphasizing air pollution as a critical public health concern. The study also emphasizes environmental science, meteorology, and atmospheric science, focusing on topics such as air pollution and health, pollutants, models, sources and chemistry, and social sciences. The findings are affirmed through rigorous discussion and review, providing a roadmap for future research, guiding decision-making processes, and expanding the knowledge frontier in the field.

The oxidative potential of airborne particulate matter in two urban areas of Chile: More than meets the eye

Oxidative potential (OP) has gained attention as a parameter that can reveal the ability of different properties of particulate matter (PM) to generate reactive oxygen species (ROS) as one single value. Moreover, OP is also believed to be a predictor of toxicity and hence the health effects of PM. This study evaluated the OP of PM₁₀, PM_2.5,and PM_1.0samples using dithiothreitol assays in two cities of Chile (Santiago and Chillán). The results showed that the OP was different between cities, PM size fractions, and seasons. Additionally, OP was strongly correlated with certain metals and meteorological variables. Higher mass-normalized OP was observed during cold periods in Chillán and warm periods in Santiago and was associated with PM_2.5 and PM₁. On the other hand, volume-normalized OP was higher during winter in both cities and for PM₁₀. Additionally, we compared the OP values to the Air Quality Index (AQI) scale and found cases of days that were classified as having "good" air quality (supposed to be less harmful to health) showing extremely high OP values that were similar to those on days that were classified as "unhealthy". Based on these results,we suggest using the OP as a complementary measure to the PM mass concentration because it includes important new information related to PM properties and compositions that could help improvecurrent air quality management tools.

Molecular characterization of organic aerosol in winter from Beijing using UHPLC-Orbitrap MS

The urban organic aerosol (OA) may pose a serious threat to human health and ecological environment. In order to understand the molecular characteristics of organic compounds in aerosols, atmospheric PM_2.5 samples were collected in Beijing and the extracts were analyzed by liquid chromatography-Orbitrap mass spectrometry combined with negative-ion electrospray ionization, positive-ion electrospray ionization, and positive-ion atmospheric pressure photoionization sources. The combination of multiple ionization sources realized the comprehensive molecular characterization of organic compounds in OA, and 1976 (+APPI), 3038 (-ESI), and 4376 (+ESI) molecular formulas were identified in this study. Significant differences in the species, abundance, and number of subgroups (CHO, CHN, CHON, CHONS, CHOS, and CH compounds) were clarified. Chemical fingerprinting of organics in the PM_2.5 extract were investigated by high-throughput non-target compound analytical methods. Structure induction of organic compounds was realized through fragmentation prediction of MS/MS spectra with Sirius software. Furthermore, a total of 50 nitroaromatic formulas, 285 organosulfates (OS) formulas, 57 nitrooxy-OS formulas, 228 CHO- formulas with carboxyl groups, and 36 monoketone formulas were determined based on diagnostic fragmentation filtering. Our results provide important insights into the molecular composition and structural characteristics of OA, and establish foundation for exploring the interaction between composition and physicochemical properties.

Deep winter intrusions of urban black carbon into a canyon near Santiago, Chile: A pathway towards Andean glaciers

Black carbon transport from the Santiago Metropolitan Area, Chile, up to the adjacent Andes Cordillera and its glaciers is of major concern. Its deposition accelerates the melting of the snowpack, which could lead to stress on water supply in addition to climate feedback. A proposed pathway for this transport is the channelling through the network of canyons that connect the urban basin to the elevated summits, as suggested by modelling studies, although no observations have validated this hypothesis so far. In this work, atmospheric measurements from a dedicated field campaign conducted in winter 2015, under severe urban pollution conditions, in Santiago and the Maipo canyon, southeast of Santiago, are analysed. Wind (speed and direction) and particulate matter concentrations measured at the surface and along vertical profiles, demonstrate intrusions of thick layers (up to 600 m above ground) of urban black carbon deep into the canyon on several occasions. Transport of PM down-valley occurs mostly through shallow layers at the surface except in connection with deep valley intrusions, when a secondary layer in altitude with return flow (down-valley) at night is observed. The transported particulate matter is mostly from the vicinity of the entrance to the canyon and uncorrelated to concentrations observed in downtown Santiago. Reanalyses data show that for 10% of the wintertime days, deep intrusions into the Maipo canyon are prevented by easterly winds advecting air pollutants away from the Andes. Also, in 23% of the cases, intrusions proceed towards a secondary north-eastward branch of the Maipo canyon, leaving 67% of the cases with favourable conditions for deep penetrations into the main Maipo canyon. Reanalyses show that the wind directions associated to the 33% anomalous cases are related to thick cloud cover and/or the development of coastal lows.

Chemical Investigation of Household Solid Fuel Use and Outdoor Air Pollution Contributions to Personal PM2.5 Exposures

In communities with household solid fuel use, transitioning to clean stoves/fuels often results in only moderate reductions in fine particulate matter (PM2.5) exposures; the chemical composition of those exposures may help explain why. We collected personal exposure (men and women) and outdoor PM2.5 samples in villages in three Chinese provinces (Shanxi, Beijing, and Guangxi) and measured chemical components, including water-soluble organic carbon (WSOC), ions, elements, and organic tracers. Source contributions from chemical mass balance modeling (biomass burning, coal combustion, vehicles, dust, and secondary inorganic aerosol) were similar between outdoor and personal PM2.5 samples. Principal component analysis of organic and inorganic components identified analogous sources, including a regional ambient source. Chemical components of PM2.5 exposures did not differ significantly by gender. Participants using coal had higher personal/outdoor (P/O) ratios of coal combustion tracers (picene, sulfate, As, and Pb) than those not using coal, but no such trend was observed for biomass burning tracers (levoglucosan, K+, WSOC). Picene and most levoglucosan P/O ratios exceeded 1 even among participants not using coal and biomass, respectively, indicating substantial indirect exposure to solid fuel emissions from other homes. Contributions of community-level emissions to exposures suggest that meaningful exposure reductions will likely require extensive fuel use changes within communities.

Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June-September) and short rain season (February-April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public's health.

Major atmospheric particulate matter sources for glaciers in Coquimbo Region, Chile

Tapado Glacier is a subtropical mountain glacier in the Coquimbo region of Chile that has been continuously retreating during the last 60 years due to diminishing precipitation rates and rising temperatures and likely due to a currently unknown influence from atmospheric pollutant deposition. Climatic and meteorological impacts on this, and other, Andean glacier have been previously studied; however, cryosphere changes driven by aerosols are still largely unknown. To contribute to the understanding of the origin of aerosols and their dispersion, this study aims to identify natural and anthropogenic sources of air pollution deposited on the Tapado Glacier (4500-5536 m a.s.l.) and their transport by using a receptor model (positive matrix factorization) together with the concentration of major ions as proxies of air pollution deposited on this glacier. This model's outcomes were complemented with daily wind backward trajectories computed for a whole year using the HYSPLYT meteorological model. Four sources were identified as the main contributors to major soluble ions in the Tapado surface snow. These sources are natural Aeolian dust (38%) from the Atacama Desert (including mining sites), natural weathered sulphates (27%), anthropogenic nitrates (25%), and coastal aerosols (10%). Coastal nitrate emissions and coastal aerosols are both sources with an important anthropogenic component, coming from La Serena and Coquimbo's coastal cities. The crustal components and sulphate profiles are similar to detritus dispersed from the glacier after wind erosion. Although the glacier is located over 4000 m above sea level, anthropogenic pollutants reached this location. However, their contributions were smaller compared to natural contaminants. Our findings can likely be extended to the nearest glaciers in Northern Chile, which have similar potential contaminant sources from cities, ports, and thriving mining activity. However, these findings may not be suitable for southern Chilean glaciers, which are closer to bigger cities and to smoke from residential heating prevalent in winter months and wildfires during the summer.

Source contributions to multiple toxic potentials of atmospheric organic aerosols

Fine particulate matter (PM_2.5) in the atmosphere is of high priority for air quality management efforts to address adverse health effects in human. We believe that emission control policies, which are traditionally guided by source contributions to PM mass, should also consider source contributions to PM health effects or toxicity. In this study, we estimated source contributions to the toxic potentials of organic aerosols (OA) as measured by a series of chemical and in-vitro biological assays and chemical mass balance model. We selected secondary organic aerosols (SOA), vehicles, biomass open burning, and cooking as possible important OA sources. Fine particulate matter samples from these sources and parallel atmospheric samples from diverse locations and seasons in East Asia were collected for the study. The source and atmospheric samples were analyzed for chemical compositions and toxic potentials, i.e. oxidative potential, inflammatory potential, aryl hydrocarbon receptor (AhR) agonist activity, and DNA-damage, were measured. The toxic potentials per organic carbon (OC) differed greatly among source and ambient particulate samples. The source contributions to oxidative and inflammatory potentials were dominated by naphthalene-derived SOA (NapSOA), followed by open burning and vehicle exhaust. The AhR activity was dominated by open burning, followed by vehicle exhaust and NapSOA. The DNA damage was dominated by vehicle exhaust, followed by open burning. Cooking and biogenic SOA had smaller contributions to all the toxic potentials. Regarding atmospheric OA, urban and roadside samples showed stronger toxic potentials per OC. The toxic potentials of remote samples in summer were consistently very weak, suggesting that atmospheric aging over a long time decreased the toxicity. The toxic potentials of the samples from the forest and the experimentally generated biogenic SOA were low, suggesting that toxicity of biogenic primary and secondary particles is relatively low.

A Review on Atmospheric Analysis Focusing on Public Health, Environmental Legislation and Chemical Characterization

Atmospheric pollution has been considered one of the most important topics in environmental science once it can be related to the incidence of respiratory diseases, climate change, and others. Knowing the composition of this complex and variable mixture of gases and particulate matter is crucial to understand the damages it causes, help establish limit levels, reduce emissions, and mitigate risks. In this work, the current scenario of the legislation and guideline values for indoor and outdoor atmospheric parameters will be reviewed, focusing on the inorganic and organic compositions of particulate matter and on biomonitoring. Considering the concentration level of the contaminants in air and the physical aspects (meteorological conditions) involved in the dispersion of these contaminants, different approaches for air sampling and analysis have been developed in recent years. Finally, this review presents the importance of data analysis, whose main objective is to transform analytical results into reliable information about the significance of anthropic activities in air pollution and its possible sources. This information is a useful tool to help the government implement actions against atmospheric air pollution.

Trends in particle matter and its elemental composition in Santiago de Chile, 2011 - 2018

Daily fine (PM_2.5) and coarse (PM_10-2.5) particle matter (PM) samples collected at Parque O'Higgins station in downtown Santiago de Chile have been studied to find the trends in concentration from 1998 to 2018. Elemental concentration was obtained using X-ray fluorescence (XRF). Regression models from previous studies indicate that the PM_2.5 and PM_10-2.5 fractions have had a continuous decrease since 1988 mostly due to several policy control measures carried out over several decades. PM_2.5 has decreased from 68.3 in 1988 to 27.6 μg/m³ in 2018 (60.4%). However, if only the last 8 years are considered (2011-2018), a leveling off can be observed in PM_10-2.5 and PM_2.5, which points to a change in the tendency. Cluster analysis of the elements in the fine and coarse fractions were identified to evaluate trends in the contributing sources. In the fine fraction, the mass contribution of crustal elements (Si, Al, Ca, and Fe) has remained stable in the last 8 years, and mass contribution of elements (Pb, Br, and Cl) associated to anthropogenic sources (traffic, wood burning) has also remained stable in the same period. For the coarse fraction, the contribution of one group of elements associated to crustal or anthropogenic sources has remained stable, and another group has decreased in the last 8 years. The leveling off can be ascribed to decreased rainfall during the last 8 years that have promoted soil dryness and resuspension of dust facilitated by wind or vehicular traffic. Mean temperatures have increased in the last 30 years, but have not contributed directly to the leveling of the concentration.Implications: Regression models indicate that the PM_2.5 (fine) and PM_10-2.5 (coarse) fractions at Parque O'Higgins station in Santiago de Chile have had a continuous decrease since 1988 mostly due to several policy control measures carried out over several decades. However, in the last 8 years (2011-2018), a leveling off can be observed in PM_10-2.5 and PM_2.5. X-ray fluorescence (XRF) analysis was performed in the fine fractions indicating that the mass contribution of crustal elements (Ca, Al, Si, Fe) to the fine fraction has remained stable. This phenomenon can be ascribed to decreased rainfall during the last 8 years that have promoted soil dryness and resuspension of dust facilitated by wind or vehicular traffic. The crustal elements in the coarse fraction have also remained stable.

Monitoring of particulate matter (PM2.5 and PM10) in San Juan city, Argentina, using active samplers and the species Tillandsia capillaris

The concentration of particulate matter (PM2.5 and PM10) was studied in San Juan city, Argentina, during winter and spring of 2017. Samplers of particulate matter (PM) and individuals of the plant species Tillandsia capillaris were placed in the centre of the city to be used as a biomonitors of atmospheric particulate matter. The PM filters and PM deposited in T. capillaris leaves were analysed to measure particle concentration and concentrations of elements (K, Ca, Mn, Fe, Cu, Zn, Br, Sr, Ba and Pb) using X-ray fluorescence by synchrotron radiation (SR-XRF). Linear regression analysis showed significant positive correlations between PM concentration in the atmosphere and the particles deposited on T. capillaris leaves. The elements quantified in PM2.5 and PM10 filters were subjected to a principal component analysis, which showed the presence of three emission sources in the study area (soil, vehicular traffic and industry) in both fractions. It was not possible to conduct this analysis with the elements obtained from the extraction of T. capillaris leaves, since most of them are solubilised at the moment of extraction. Biomonitoring with T. capillaris might be used to estimate the concentration of particulate matter in large areas or in remote sites with no electrical power supply to run active samplers. Further studies should be carried out in other regions, and more variables should be incorporated to obtain increasingly deterministic models.

A Clustering Framework to Reveal the Structural Effect Mechanisms of Natural and Social Factors on PM2.5 Concentrations in China

Understanding the mechanisms of various factors that affect PM2.5 can assist in the development of scientific measures to improve air quality. Nevertheless, existing research has concentrated on exploring local effect mechanisms, while structural effect mechanisms at regional or national scales have scarcely been analysed. Consequently, this study presents an analytical framework for elucidating the structural effect mechanisms of associated factors on PM2.5. Geographically and temporally weighted regression was used to explore the local effect mechanisms. This was followed by spatial clustering analysis to reveal these mechanisms by detecting their aggregation patterns. In the analysis, datasets for annual mean PM2.5 and socio-economic factors in China from 1999 to 2016 were employed. Urban population, gross industrial output, and sulphur dioxide emissions were identified as factors affecting changes in PM2.5 concentrations. These three factors had both negative and positive effects, while the gross industrial output had the largest coefficient variation degree. Three geographically related factors exhibited different impacts on PM2.5 concentrations in most of mainland China. These factors were the urban population roughly west of the Heihe-Tengchong line, gross industrial output primarily in southwestern China, and sulphur dioxide emissions primarily in southern China.

Combining Cluster Analysis of Air Pollution and Meteorological Data with Receptor Model Results for Ambient PM2.5 and PM10

Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM2.5 and PM10. We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.

Seasonal variations in PM10 inorganic composition in the Andean city

Particulate matter (PM) is one of the key pollutants causing health risks worldwide. While the preoccupation for increased concentrations of these particles mainly depends on their sources and thus chemical composition, some regions are yet not well investigated. In this work the composition of chemical elements of atmospheric PM₁₀ (particles with aerodynamic diameters ≤ 10 µm), collected at the urban and suburban sites in high elevation tropical city, were chemically analysed during the dry and wet seasons of 2017-2018. A large fraction (~ 68%) of PM₁₀ composition in Quito, Ecuador is accounted for by water-soluble ions and 16 elements analysed using UV/VIS spectrophotometer and Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Hierarchical clustering analysis was performed to study a correlation between the chemical composition of urban pollution and meteorological parameters. The suburban area displays an increase in PM₁₀ concentrations and natural elemental markers during the dry (increased wind intensity, resuspension of soil dust) season. Meanwhile, densely urbanized area shows increased total PM₁₀ concentrations and anthropogenic elemental markers during the wet season, which may point to the worsened combustion and traffic conditions. This might indicate the prevalence of cardiovascular and respiratory problems in motorized areas of the cities in the developing world.

Chemical Characterization and Seasonality of Ambient Particles (PM2.5) in the City Centre of Addis Ababa

Ambient air pollution is a growing public health concern in major African cities, including Addis Ababa (Ethiopia), where little information is available on fine particulate matter (PM2.5, with aerodynamic diameter <2.5 µm) pollution. This paper aims to characterize annual PM2.5, including bulk composition and seasonal patterns, in Addis Ababa. We collected 24-h PM2.5 samples in the central city every 6 days from November 2015 to November 2016. The mean (±SD) daily PM2.5 concentration was 53.8 (±25.0) µg/m3, with 90% of sampled days exceeding the World Health Organization's guidelines. Principal components were organic matter (OM, 44.5%), elemental carbon (EC, 25.4%), soil dust (13.5%), and SNA (sulfate, nitrate, and ammonium ions, 8.2%). Higher PM2.5 concentrations were observed during the heavy rain season, while crustal dust concentrations ranged from 2.9 to 37.6%, with higher levels during dry months. Meteorological variables, vehicle emissions, biomass fuels, unpaved roads, and construction activity contribute to poor air quality. Compared to the Air Quality Index (AQI), 31% and 36% of observed days were unhealthy for everyone and unhealthy for sensitive groups, respectively. We recommend adopting effective prevention strategies and pursuing research on vehicle emissions, biomass burning, and dust control to curb air pollution in the city.

Source Apportionment of Coarse Particulate Matter (PM10) in Yangon, Myanmar

The Republic of the Union of Myanmar is one of many developing countries facing concerns about particulate matter (PM). Previously, a preliminary study of PM_2.5 in 2018 suggested that the main source of PM in Yangon, the former capital, was vehicle emissions. However, this suggestion was not supported by any chemical composition data. In this study, to fill that gap, we quantitatively determined source contributions to coarse particulate matter (PM₁₀) in Yangon, Myanmar. PM₁₀ samples were collected in Yangon from May 2017 to April 2018 and chemically analyzed to determine composition. Chemical composition data for these samples were then used in the Chemical Mass Balance (CMB) model to identify the major sources of particulate matter in this area. The results indicate that PM₁₀ composition varies seasonally according to both meteorological factors (e.g., precipitation and temperature) and human activities (e.g., firewood and yard waste burning). The major sources of PM in Yangon annually were dust, secondary inorganic aerosols (SIA), and secondary organic aerosols (SOA), while contributions from biomass burning were more important during the winter months.

Ambient particulate matter in Santiago, Chile: 1989-2018: A tale of two size fractions

We have analyzed trends in ambient fine (PM_2.5) and coarse (PM_2.5-10) particulate matter in Santiago, Chile, for the last 30 years. PM_2.5 has monotonously decreased between 67% and 72% at those sites. Trends varied between -2.0 and -2.7 (μg/m³/year) between 1989 and late 90's, and between -0.7 and -1.1 (μg/m³/year) afterwards. This slowing down is likely a consequence of fast increase of motor vehicles in the city, which have become a dominant source of ambient PM_2.5. Annual ambient PM_2.5 concentrations are still above 20 (μg/m³), so more regulation is needed to bring them down. Coarse particles have changed little in 30 years, decreasing between 0% and 12%; particle concentrations have evolved in a non-linear way: first increasing in 1989-1995, then decreasing until 2003, and with a flat trend afterwards. We ascribe these trends to a combination of a) public works implemented throughout the city, b) fugitive dust controls like street sweeping programs and emission offsets for PM₁₀ and c) increasing numbers of motor vehicles in the city. Further initiatives are needed to curb down coarse particles as well. By considering interaction between trend and seasonality, we have found that ambient PM_2.5 has monotonously decreased all year long at all monitoring sites with similar patterns; this is characteristic of a regional-scale pollution. For ambient PM_2.5-10 trend and season have a more complex, site-specific interaction, suggesting local sources and site location in the basin are relevant in determining ambient concentrations of coarse particles. A limitation of this study is that no quantitative link between ambient concentrations trends and atmospheric emissions could be established with the analyses carried out. A strength of the study is the long period analyzed with measurements conducted with the same gravimetric methodology.

Source apportionment of fine particulate matter in a Middle Eastern Metropolis, Tehran-Iran, using PMF with organic and inorganic markers

With over 8 million inhabitants and 4 million motor vehicles on the streets, Tehran is one of the most crowded and polluted cities in the Middle East. Frequent exceedances of national daily PM_2.5 limit have been reported in this city during the last decade, yet, the chemical composition and sources of fine particles are poorly determined. In the present study, 24-hour PM_2.5 samples were collected at two urban sites during two separate campaigns, a one-year period from 2014 to 2015 and another three-month period at the beginning of 2017. Concentrations of organic carbon (OC), elemental carbon (EC), inorganic ions, trace metals and specific organic molecular markers were measured by chemical analysis of filter samples. The dominant mass components were organic matter (OM), sulfate and EC. With a 20% water-soluble organic carbon (WSOC) fraction, the predominance of primary anthropogenic sources (i.e. fossil fuel combustion) was anticipated. A positive matrix factorization (PMF) analysis using the ME-2 (Multilinear Engine-2) solver was then applied to this dataset. 5 factors were identified by Marker-PMF, named as traffic exhaust (TE), biomass burning (BB), industries (Ind.), nitrate-rich and sulfate-rich. Another 4 factors were identified by Metal-PMF, including, dust, vehicles (traffic non-exhaust, TNE), industries (Ind.) and heavy fuel combustion (HFC). Traffic exhaust was the dominant source with 44.5% contribution to total quantified PM_2.5 mass. Sulfate-rich (24.2%) and nitrate-rich (18.4%) factors were the next major contributing sources. Dust (4.4%) and biomass burning (6.7%) also had small contributions while the total share of all other factors was < 2%. Investigating the correlations of different factors between the two sampling sites showed that traffic emissions and biomass burning were local, whereas dust, heavy fuel combustion and industrial sources were regional. Results of this study indicate that gas- and particle-phase pollutants emitted from fossil fuel combustion (mobile and stationary) are the principal origin of both primary and secondary fine aerosols in Tehran.

A Methodology for Data-Driven Decision-Making in the Monitoring of Particulate Matter Environmental Contamination in Santiago of Chile

Atmospheric pollution derives mainly from anthropogenic activities that use combustion and may lead to adverse effects in exposed populations. It is generally accepted that air contamination causes cardiovascular and pulmonary morbidity in addition to increased mortality after exposure, but other epidemiological associations have also been described, including cancer as well as reproductive and immunological toxicity. Thus the concentration of chemicals in the air must be controlled. We propose that monitoring of air quality may be achieved by employing data analytics to generate information within the context of data-driven decision making to prevent and/or adequately alert the population about possible critical episodes of air contamination. In this paper, we propose a methodology for monitoring particulate matter pollution in Santiago of Chile which is based on bivariate control charts with heavy-tailed asymmetric distributions. This methodology is useful for monitoring environmental risk when the particulate matter concentrations follow bivariate Birnbaum-Saunders or Birnbaum-Saunders-t-Student distributions. A case study with real particulate matter pollution from Santiago is provided, which shows that the methodology is suitable to alert early episodes of extreme air pollution. The results are in agreement with the critical episodes reported with the current model used by the Chilean health authority.

PM2.5 Pollution in Xingtai, China: Chemical Characteristics, Source Apportionment, and Emission Control Measures

Beijing-Tianjin-Hebei (BTH) and its surrounding areas are one of the most polluted regions in China. Xingtai, as a heavy industrial city of BTH and its surrounding areas, has been experiencing a severe PM2.5 pollution in recent years, characterized by extremely high concentrations of PM2.5. In 2014, PM2.5 mass concentrations monitored by online instruments in urban areas of Xingtai were 116, 77, 128, and 200 µg m−3 in spring, summer, autumn and winter, respectively, with annually average concentrations of 130 µg m−3 exhibiting 3.7 times higher than National Ambient Air Quality Standard (NAAQS) value for PM2.5 (35 µg m−3). To identify PM2.5 emission sources, ambient PM2.5 samples were collected during both cold and warm periods in 2014 in urban areas of Xingtai. Organic carbon (OC), sulfate, nitrate, ammonium and elemental carbon (EC) were the dominant components of PM2.5, accounting for 13%, 11%, 12%, 11% and 8% in the cold period, respectively, and 11%, 12%, 9%, 6%, and 5% in the warm period, respectively. Source apportionment results indicated that coal combustion (24.4%) was the largest PM2.5 emission source, followed by secondary sulfate (22.2%), secondary nitrate (18.4%), vehicle exhaust dust (12.4%), fugitive dust (9.7%), construction dust (5.5%), soil dust (3.4%) and metallurgy dust (1.6%). Based on PM2.5 source apportionment results, some emission control measures, such as replacing bulk coal with clean energy sources, controlling coal consumption by coal-fired boiler upgrades, halting operations of unlicensed small polluters, and controlling fugitive and VOCs emission, were proposed to be implemented in order to improve Xingtai’s ambient air quality.

Microclimate simulation and model optimization of the effect of roadway green space on atmospheric particulate matter

Urban green spaces have the potential to mitigate and regulate atmospheric pollution. However, existing studies have primarily focused on the adsorption effect of different plants on atmospheric particulate matter (PM), whereas the effect of green space on PM has not been adequately addressed. In this study, the effect of different urban green space structures and configurations on PM was investigated through the 3D computational fluid dynamics (CFD) model ENVI-met by treating the green space as a whole based on field monitoring, and at the same time, the regulatory effect of green space on PM was examined by integrating information about the forest stand, PM concentration, and meteorological factors. The results show that the green space primarily affected wind speed but had no significant effect on relative humidity, temperature, or wind direction (P > 0.05). The PM concentration was significantly positively correlated with the relative humidity (P < 0.01), significantly negatively correlated with temperature (P < 0.05), but not significantly correlated with wind speed and direction (P > 0.05). Comparison with the measured values reveals that the ENVI-met model well reflected the differences in PM concentrations between different green spaces and the effect of green space on PM. In different green space structures, the uniform-type structure performed rather poorly at purifying PM, the concave-shaped structure performed the best, and the purifying effectiveness of the incremental-type and convex-shaped structure of green space was higher in the rear region than in the front region; in contrast, the degressional-type green space structure was prone to cause aggregation of the PM in the middle region. Broadleaf and broadleaf mixed forests had a better purifying effectiveness on PM than did coniferous forests, mixed coniferous forests, and coniferous broadleaf mixed forests. The above results are of great significance for urban planning and maximizing the use of urban green space resources.

Observations of particulate matter, NO2, SO2, O3, H2S and selected VOCs at a semi-urban environment in the Amazon region

This research aims to assess air quality in a transitional location between city and forest in the Amazon region. Located downwind of the Manaus metropolitan region, this study is part of the large-scale experiment GoAmazon2014/5. Based on their pollutant potential, inhalable particulate matter (PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), hydrogen sulfide (H₂S), benzene, toluene, ethylbenzene and meta-, orto-, para-xylene (BTEX) were selected for analysis. Sampling took place during the wet season (March-April 2014) and dry season (August-October 2014). The number of forest fires in the surroundings was higher during the dry wet season. Results show significant increase during the dry season in mass concentration (wet: <0.01-10 μg m^-3; dry: 9.8-69 μg m^-3), NH₄⁺ soluble content (wet: 13-125 μg m^-3; dry: 86-323 μg m^-3) and K⁺ soluble content (wet: 11-168 μg m^-3; dry 60-356 μg m^-3) of the PM_2.5, and O₃ levels (wet: 1.4-14 μg m^-3; dry: 1.0-40 μg m^-3), indicating influence of biomass burning emissions. BTEX concentrations were low in both periods, but also increased during the dry season. A weak correlation in the time series of the organic and inorganic gaseous pollutants indicates a combination of different sources in both seasons and NO2 results suggest a spatial heterogeneity in gaseous pollutants levels beyond initial expectations.

Chemical Characterization of PM2.5 at Rural and Urban Sites around the Metropolitan Area of Huancayo (Central Andes of Peru)

The purpose of this study was to determine PM2.5 mass concentration and the contents of trace elements and water-soluble ions in samples collected inside the Metropolitan area of Huancayo. Four monitoring stations were installed at three urban areas (UNCP, HYO, and CHI) and one rural (IGP). The sampling campaign was carried out from March 2017 to November 2017. The PM2.5 content was determined by gravimetric method, and fifteen trace elements (TE) and seven water-soluble ions were detected by inductively coupled plasma mass spectrometry (ICP–MS), and ion chromatography (IC), respectively. Datasets were assessed by one ANOVA test to detect significant differences among monitoring station. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied for source identification. The mean annual concentration of PM2.5 mass concentrations has ranged (average) from 3.4 to 36.8 µg/m3 (16.6 ± 6.8 µg/m3) for the monitoring stations under study. The annual World Health Organization thresholds and national air quality standards were exceeded. Significant differences (p < 0.05) were observed between most trace elements at urban and rural areas. PCA and HCA illustrated that the most important sources of traces element originated of natural origin (soil re-suspension) and vehicular sources (fuel combustion, abrasion of vehicles tires, wear car components).

Chemical composition and source apportionment of ambient, household, and personal exposures to PM2.5 in communities using biomass stoves in rural China

Fine particulate matter (PM_2.5) has health effects that may depend on its sources and chemical composition. Few studies have quantified the composition of personal and area PM_2.5 in rural settings over the same time period. Yet, this information would shed important light on the sources influencing personal PM_2.5 exposures. This study investigated the sources and chemical composition of 40 personal exposure, 40 household, and 36 ambient PM_2.5 samples collected in the non-heating and heating seasons in rural southwestern China. Chemical analysis included black carbon (BC), water-soluble components (ions, organic carbon), elements, and organic tracers. Source apportionment was conducted using organic tracer concentrations in a Chemical Mass Balance model. Biomass burning was the largest identified PM_2.5 source contributor to household (average, SD: 48 ± 11%) and exposures (31 ± 6%) in both seasons, and ambient PM_2.5 in winter (20 ± 4%). Food cooking also contributed to household and personal PM, reaching approximately half of the biomass contributions. Secondary inorganic aerosol was the major identified source in summertime ambient PM_2.5 (32 ± 14%), but was present in all samples (summer: 10 ± 3% [household], 13 ± 6% [exposures]; winter: 18 ± 2% [ambient], 7 ± 2% [household], 8 ± 2% [exposures]). Dust concentrations and fractional contribution to total PM_2.5 were higher in summer exposure samples (7 ± 4%) than in ambient or household samples (6 ± 1% and 2 ± 1%, respectively). Indoor sources comprised up to one-fifth of ambient PM_2.5, and outdoor sources (vehicles, secondary aerosols) contributed up to 15% of household PM_2.5. While household sources were the main contributors to PM_2.5 exposures in terms of mass, inorganic components of personal exposures differed from household samples. Based on these findings, health-focused initiatives to reduce harmful PM_2.5 exposures may consider a coordinated approach to address both indoor and outdoor PM_2.5 source contributors.

Exploring atmospheric stagnation during a severe particulate matter air pollution episode over complex terrain in Santiago, Chile

A severe air quality degradation event occurred in the Santiago Metropolitan Area (SMA), Chile, in June 2014. Meteorological and air quality measurements from 11 stations in the area as well as numerical simulations using the Weather and Research Forecasting (WRF) model were used to explain the main reasons for the occurrence of elevated particulate matter (PM) concentrations. The conditions were characterized with formation of a coastal low in central Chile between the southeastern anticyclone and a high-pressure system over Argentina. At a local scale, these conditions generated a depression at the base of the inversion layer, an increase in the vertical thermal stability, lower humidity and low-wind conditions, which were conducive to a decrease in pollutant dispersion and insufficient ventilation of the polluted air. Measurements and simulations using the WRF model revealed a vertical structure of the boundary layer during these stagnant conditions and provided a basis for a trajectory analysis. The back-trajectory calculation showed that the transport of air parcels was contained in the valley during the highest concentrations. The analysis also enabled the definition of the threshold values of a simple indicator of air pollution (ventilation coefficient, VC), which confirmed the evolution of the episode and divided the observed daily concentrations into two groups, with one including values above the limits prescribed by the national air quality standards (NAQS) and the other including values below these limits. For the SMA, the daily PM concentrations above the NASQ limits were associated with an overall mean threshold value of VC below 500 m² s^-1 (for PM_2.5) and 300 m² s^-1 (for PM₁₀). To apply the VC analysis to other pollutants and different geographic locations, different threshold values should be evaluated.

Seasonal trends in the composition and sources of PM2.5 and carbonaceous aerosol in Tehran, Iran

Currently PM_2.5 is a major air pollution concern in Tehran, Iran due to frequent high levels and possible adverse impacts. In this study, which is the first of its kind to take place in Tehran, composition and sources of PM_2.5 and carbonaceous aerosol were determined, and their seasonal trends were studied. In this regard, fine PM samples were collected every six days at a residential station for one year and the chemical constituents including organic marker species, metals, and ions were analyzed by chemical analysis. The source apportionment was performed using organic molecular marker-based CMB receptor modeling. Carbonaceous compounds were the major contributors to fine particulate mass in Tehran, as OC and EC together comprised on average 29% of PM_2.5 mass. Major portions of OC in Tehran were water insoluble and are mainly attributed to primary sources. Higher levels of several PAHs, which are organic tracers of incomplete combustion, and hopanes and steranes as organic tracers of mobile sources were obtained in cold months and compared to the warm months. The major contributing source to particulate OC was identified as vehicles, which contributed about 72% of measured OC. Among mobile sources, gasoline-fueled vehicles had the highest impact with a mean contribution of 48% to the measured OC. Mobile sources also were the largest contributor to total PM_2.5 (40%), followed by dust (24%) and sulfate (11%). In addition to primary emissions, mobile sources also directly and indirectly played an important role in another 27% of fine particulate mass (secondary organics and ions), which highlights the impact of vehicles in Tehran. Our results highlighted and quantified the role of motor vehicles in fine PM production, particularly during winter time. The results of this study could be used to set more effective regulations and control strategies particularly upon mobile sources.

Source apportionment of PM2.5 organic carbon in the San Joaquin Valley using monthly and daily observations and meteorological clustering

Two hundred sixty-three fine particulate matter (PM_2.5) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies. Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments.

Elemental composition of PM2.5 in the urban environment of San Juan, Argentina

This study contributes to the current knowledge about air pollution in the province of San Juan, Argentina. Sampling was carried out to measure the fine particulate matter in the atmosphere (PM_2.5) of the city of San Juan. PM_2.5 was collected continuously during the winter and spring seasons of 2014 and 2015, and the concentrations of 14 elements (Pb, Ca, K, Cd, Ni, Cr, Mn, V, Cu, Ti, Ba, Co, Sr, and Fe) were determined in PM_2.5 filters using the technique of X-ray fluorescence by synchrotron radiation (SR-XRF). The results revealed that PM_2.5 presented annual and seasonal variations, showing a higher concentration during the winter seasons. In addition, for the elements quantified in the filters, a multivariate analysis (Positive Matrix Factorization) was performed to identify the main sources of emission of these elements in the study area, with a series of components being obtained that corresponded to their compositions, which were assigned physical meanings. The first factor, which was the most important in contribution of the sum of the measured elements (45%), was determined mainly by the elements K, Ti, V, Mn, and Fe, which came predominantly from soil particles. The second factor contributed 30% to the measured species in PM_2.5, with higher Ba and Zn content perhaps being related to emissions from vehicular traffic. Finally, the third factor, in which Pb, Cr, and Ca predominated, may be an indicator of industrial activity and contributed 25% of the sum of the measured elements of PM_2.5. The results of this study provide the first PM composition database in the province, and this can now be used in the development of mitigation and prevention programs.

Climatic variability and morbidity and mortality associated with particulate matter

OBJECTIVE

The objective of this study has been to analyze whether fine particulate matter (PM_2.5), as well as its synergistic effect with maximum temperature, humidity, and seasons, is associated with morbidity and mortality from cardiovascular diseases.

METHODS

This is an ecological study of time series. We have used as outcomes the daily death and hospitalization records of adults aged 45 years and over from 2009 to 2011 of the municipalities of Cuiabá and Várzea Grande, State of Mato Grosso, Brazil. We have used Poisson regression using generalized additive models, assuming a significance level of 5%. The model has been controlled for temporal trend, seasonality, average temperature, humidity, and season effects. Daily concentrations of PM_2.5 (particulate material with aerodynamic diameter less than 2.5 micrometers) have been obtained by converting the values of optical aerosol thickness. Maximum temperature, humidity, and seasons have been separately included in the model as dummy variables for the analysis of the synergistic effect of PM_2.5 with morbidity and mortality from cardiovascular disease. We have calculated the percentage increase of relative risk (%RR) of deaths and hospitalizations for the linear increase of 10 μg/m³ of PM_2.5.

RESULTS

Between 2009 and 2011, the increase in PM_2.5 was associated with a %RR 2.28 (95%CI 0.53–4.06) for hospitalizations on the same day of exposure and RR% 3.57 (95%CI 0.82–6.38) for deaths with a lag of three days. On hot days, %RR 4.90 (95%CI -0.61–9.38) was observed for deaths. No modification of the effect of PM_2.5 was observed for maximum temperature in relation to hospitalizations. On days with low humidity, %RR was 5.35 (95%CI -0.20–11.22) for deaths and 2.71 (95%CI -0.39–5.92) for hospitalizations. In the dry season, %RR was 2.35 (95%CI 0.59–4.15) for hospitalizations and 3.43 (95%CI 0.58–6.35) for deaths.

CONCLUSIONS

The PM_2.5 is associated with morbidity and mortality from cardiovascular diseases and its effects may be potentiated by heat and low humidity and during the dry season.

Structural signatures of water-soluble organic aerosols in contrasting environments in South America and Western Europe

This study describes and compares the key structural units present in water-soluble organic carbon (WSOC) fraction of atmospheric aerosols collected in different South American (Colombia - Medellín and Bogotá, Peru - Lima, Argentina - Buenos Aires, and Brazil - Rio de Janeiro, São Paulo, and Porto Velho, during moderate (MBB) and intense (IBB) biomass burning) and Western European (Portugal - Aveiro and Lisbon) locations. Proton nuclear magnetic resonance (¹H NMR) spectroscopy was employed to assess the relative distribution of non-exchangeable proton functional groups in aerosol WSOC of diverse origin, for the first time to the authors' knowledge in South America. The relative contribution of the proton functional groups was in the order H-C > H-C-C= > H-C-O > Ar-H, except in Porto Velho during MBB, Medellín, Bogotá, and Buenos Aires, for which the relative contribution of H-C-O was higher than that of H-C-C=. The ¹H NMR source attribution confirmed differences in aging processes or regional sources between the two geographic regions, allowing the differentiation between urban combustion-related aerosol and biological particles. The aerosol WSOC in Aveiro, Lisbon, and Rio de Janeiro during summer are more oxidized than those from the remaining locations, indicating the predominance of secondary organic aerosols. Fresh emissions, namely of smoke particles, becomes important during winter in Aveiro and São Paulo, and in Porto Velho during IBB. The biosphere is an important source altering the chemical composition of aerosol WSOC in South America locations. The source attribution in Medellín, Bogotá, Buenos Aires, and Lima confirmed the mixed contributions of biological material, secondary formation, as well as urban and biomass burning emissions. Overall, the information and knowledge acquired in this study provide important diagnostic tools for future studies aiming at understanding the water-soluble organic aerosol problem, their sources and impact at a wider geographic scale.

Wood burning pollution in southern Chile: PM2.5 source apportionment using CMB and molecular markers

Temuco is a mid-size city representative of severe wood smoke pollution in southern Chile; i.e., ambient 24-h PM_2.5 concentrations have exceeded 150 μg/m³ in the winter season and the top concentration reached 372 μg/m³ in 2010. Annual mean concentrations have decreased but are still above 30 μg/m³. For the very first time, a molecular marker source apportionment of ambient organic carbon (OC) and PM_2.5 was conducted in Temuco. Primary resolved sources for PM_2.5 were wood smoke (37.5%), coal combustion (4.4%), diesel vehicles (3.3%), dust (2.2%) and vegetative detritus (0.7%). Secondary inorganic PM_2.5 (sulfates, nitrates and ammonium) contributed 4.8% and unresolved organic aerosols (generated from volatile emissions from incomplete wood combustion), including secondary organic aerosols, contributed 47.1%. Adding the contributions of unresolved organic aerosols to those from primary wood smoke implies that wood burning is responsible for 84.6% of the ambient PM_2.5 in Temuco. This predominance of wood smoke is ultimately due to widespread poverty and a lack of efficient household heating methods. The government has been implementing emission abatement policies but achieving compliance with ambient air quality standards for PM_2.5 in southern Chile remains a challenge.

The oxidative potential of PM2.5 exposures from indoor and outdoor sources in rural China

BACKGROUND

Airborne particulate matter (PM) is a widespread environmental exposure and leading health risk factor. The health effects of PM may be mediated by its oxidative potential; however, the combustion and non-combustion sources and components of PM responsible for its oxidative potential are poorly understood, particularly in low- and middle-income rural settings where coal and biomass burning for cooking and heating contribute to PM exposure.

METHODS

We measured 24-h personal exposures to fine particulate matter (PM2.5) of 20 rural women in northern (Inner Mongolia) and southern (Sichuan) Chinese provinces who used solid fuels (i.e., coal, biomass). PM2.5 exposures were characterized for mass, black carbon, water-soluble organic carbon, major water-soluble ions, and 47 elements. The oxidative potential of PM2.5 exposures was measured using acellular (dithiothreitol-based) and cellular (macrophage-based) assays. We performed factor and correlation analyses using the chemical components of PM2.5 to identify sources of exposure to PM2.5 and their chemical markers. Associations between oxidative potential and chemical markers for major sources of PM2.5 exposure were assessed using linear regression models.

RESULTS

Women's geometric mean PM2.5 exposures were 249μgm(-3) (range: 53.9-767) and 83.9μgm(-3) (range: 73.1-95.5) in Inner Mongolia and Sichuan, respectively. Dust, biomass combustion, and coal combustion were identified as the major sources of exposure to PM2.5. Markers for dust (iron, aluminum) were significantly associated with intrinsic oxidative potential [e.g., one interquartile range increase in iron (ppm) was associated with an 85.5% (95% CI: 21.5, 149) increase in cellular oxidative potential (μgZymosanmg(-1))], whereas markers for coal (arsenic, non-sulfate sulfur) and biomass (black carbon, cadmium) combustion were not associated with oxidative potential.

CONCLUSIONS

Dust was largely responsible for the intrinsic oxidative potential of PM2.5 exposures of rural Chinese women, whereas biomass and coal combustion were not significantly associated with intrinsic oxidative potential.

Seasonal and spatial differences in source contributions to PM2.5 in Wuhan, China

Fine particle (PM2.5) samples were collected in 2011 and 2012 simultaneously at three sites in Wuhan in an industrial area (ID), downtown Wuhan (DT), and the Wuhan botanical gardens (BG). The annual average concentration of PM2.5 was highest in the industrial area at 180μgm-3 and lowest in the botanical gardens, with an average of 93μgm-3. The average downtown PM2.5 concentration was 113μgm-3. All sites had concentrations well above the World Health Organization (WHO) guidelines and the Chinese air quality standard. The concentration of major constituents of PM2.5 varied seasonally across all sites; specifically, sulfate, nitrate, and organic carbon varied most strongly during spring, followed by summer and fall. Organic carbon varied the most across sites for all seasons, which is attributable to large differences in local source emissions. The major primary sources contributing to OC were vehicle emissions (38.1±8.3%), coal combustion (7.0±6.2%), meat cooking (3.0±1.6%), and biomass burning (3.0±1.0%). All these sources had large seasonal variations across the three sites. Biomass burning had the largest impact at BG, mobile sources had the largest impact at DT, and coal combustion had the largest impact at ID. Mineral dust was a major contributor to PM2.5 (average 16.8±9.6μgm-3) and had very homogenous concentrations across the sites during springtime due to regional dust storms, but had much higher concentration at ID during the summer and fall. The results demonstrate the need for both regional and local air pollution control strategies to reduce air pollution in Wuhan. This research contributes to the field of particulate matter studies by providing information about seasonal and regional fluctuations in PM2.5 in large urban areas, which helps advance understanding of the sources responsible for urban haze.

Source insights into the 11-h daytime and nighttime fine ambient particulate matter in China as well as the synthetic studies using the new Multilinear Engine 2-species ratios (ME2-SR) method

Modeled results are very important for environmental management. Unreasonable modeled result can lead to wrong strategy for air pollution management. In this work, an improved physically constrained source apportionment (PCSA) technology known as Multilinear Engine 2-species ratios (ME2-SR) was developed to the 11-h daytime and nighttime fine ambient particulate matter in urban area. Firstly, synthetic studies were carried out to explore the effectiveness of ME2-SR. The estimated source contributions were compared with the true values. The results suggest that, compared with the positive matrix factorization (PMF) model, the ME2-SR method could obtain more physically reliable outcomes, indicating that ME2-SR was effective, especially when apportioning the datasets with no unknown source. Additionally, 11-h daytime and nighttime PM2.5 samples were collected from Tianjin in China. The sources of the 11-h daytime and nighttime fine ambient particulate matter in China were identified using the new method and the PMF model. The calculated source contributions for ME2-SR for daytime PM2.5 samples are resuspended dust (38.91 μg m(-3), 26.60%), sulfate and nitrate (38.60 μg m(-3), 26.39%), vehicle exhaust and road dust (38.26 μg m(-3), 26.16%) and coal combustion (20.14 μg m(-3), 13.77%), and those for nighttime PM2.5 samples are resuspended dust (18.78 μg m(-3), 12.91%), sulfate and nitrate (41.57 μg m(-3), 28.58%), vehicle exhaust and road dust (38.39 μg m(-3), 26.39%), and coal combustion (36.76 μg m(-3), 25.27%). The comparisons of the constrained versus unconstrained outcomes clearly suggest that the physical meaning of the ME2-SR results is interpretable and reliable, not only for the specified species values but also for source contributions. The findings indicate that the ME2-SR method can be a useful tool in source apportionment studies, for air pollution management.

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012

Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m(3)] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor-outdoor correlation (log-transformed concentrations) was low: R=-0.06, 95% CI: (-0.35 to 0.24), likely owing to outdoor spatial variability. A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations. For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels.

Seasonal and regional variations of source contributions for PM10 and PM2.5 in urban environment

To characterize the sources of to PM10 and PM2.5, a long-term, speciate and simultaneous dataset was sampled in a megacity in China during the period of 2006-2014. The PM concentrations and PM2.5/PM10 were higher in the winter. Higher percentages of Al, Si, Ca and Fe were observed in the summer, and higher concentrations of OC, NO3(-) and SO4(2-) occurred in the winter. Then, the sources were quantified by an advanced three-way model (defined as an ABB three-way model), which estimates different profiles for different sizes. A higher percentage of cement and crustal dust was present in the summer; higher fractions of coal combustion and nitrate+SOC were observed in the winter. Crustal and cement contributed larger portion to coarse part of PM10, whereas vehicular and secondary source categories were enriched in PM2.5. Finally, potential source contribution function (PSCF) and source regional apportionment (SRA) methods were combined with the three-way model to estimate geographical origins. During the sampling period, the southeast region (R4) was an important region for most source categories (0.6%-11.5%); the R1 (centre region) also played a vital role (0.3-6.9%).

Characterization of PM2.5 in Guangzhou, China: uses of organic markers for supporting source apportionment

Organic carbon (OC), elemental carbon (EC), and non-polar organic compounds including n-alkanes (n-C14-n-C40), polycyclic aromatic hydrocarbons (PAHs), phthalate esters (PAEs) and hopanes were quantified in fine particulate (PM2.5), which were collected in urban area of Guangzhou, China in winter and summer in 2012/2013. The pollutants levels were well comparable with the data obtained in previous studies in Pearl River Delta (PRD) region but much lower than most northern Chinese megacities. The contribution of EC to PM2.5 and OC/EC ratio suggest that the pollution sources were relatively consistent in GZ between the two seasons. Benzo[a]pyrene (BaP) was the most abundant PAHs, which were 4.9 and 1.0ng/m(3) on average, accounting for 10.7% and 9.1% to the total quantified PAHs in winter and summer, respectively. The total concentrations of PAEs ranged from 289.1 to 2435ng/m(3) and from 102.4 to 1437ng/m(3), respectively, in winter and summer. Di-n-butyl phthalate (DBP) was the most dominant PAEs. The ambient levels of PAEs could be partly attributed to the widespread uses of the household products, municipal garbage compressing, sewage, and external painting material on the building. Source apportionment for OC with chemical mass balance (CMB) model demonstrated coal combustion, vehicle emission, cooking, and secondary organic compounds (SOC) formation were the four major pollution sources. Both of the indices of n-alkanes and diagnostic PAHs ratios support that anthropogenic sources such as vehicle emission and coal combustion were the significant pollution sources with some extents from epicuticular waxes by terrestrial plants. The ratio of hopanes to EC proved the influences from vehicle emission, and displayed a certain degree of the air aging in the Guangzhou ambient air.

Status and characteristics of ambient PM2.5 pollution in global megacities

Ambient PM2.5 pollution is a substantial threat to public health in global megacities. This paper reviews the PM2.5 pollution of 45 global megacities in 2013, based on mass concentration from official monitoring networks and composition data reported in the literature. The results showed that the five most polluted megacities were Delhi, Cairo, Xi'an, Tianjin and Chengdu, all of which had an annual average concentration of PM2.5 greater than 89μg/m(3). The five cleanest megacities were Miami, Toronto, New York, Madrid and Philadelphia, the annual averages of which were less than 10μg/m(3). Spatial distribution indicated that the highly polluted megacities are concentrated in east-central China and the Indo-Gangetic Plain. Organic matter and SNA (sum of sulfate, nitrate and ammonium) contributed 30% and 36%, respectively, of the average PM2.5 mass for all megacities. Notable seasonal variation of PM2.5 polluted days was observed, especially for the polluted megacities of China and India, resulting in frequent heavy pollution episodes occurring during more polluted seasons such as winter. Marked differences in PM2.5 pollution between developing and developed megacities require more effort on local emissions reduction as well as global cooperation to address the PM2.5 pollution of those megacities mainly in Asia.