scholarly journals AIRUSE-LIFE+: a harmonized PM speciation and source apportionment in five southern European cities

2016 ◽  
Vol 16 (5) ◽  
pp. 3289-3309 ◽  
Author(s):  
Fulvio Amato ◽  
Andrés Alastuey ◽  
Angeliki Karanasiou ◽  
Franco Lucarelli ◽  
Silvia Nava ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Urban Areas ◽  
The Other ◽  
Saharan Dust ◽  
Industrial Emissions ◽  
Large Variability ◽  
Pm10 And Pm2.5 ◽  
Local Dust

Abstract. The AIRUSE-LIFE+ project aims at characterizing similarities and heterogeneities in particulate matter (PM) sources and contributions in urban areas from southern Europe. Once the main PMx sources are identified, AIRUSE aims at developing and testing the efficiency of specific and non-specific measures to improve urban air quality. This article reports the results of the source apportionment of PM10 and PM2.5 conducted at three urban background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB and MLN-UB), one suburban background site (Athens, ATH-SUB) and one traffic site (Porto, POR-TR). After collecting 1047 PM10 and 1116 PM2.5 24 h samples during 12 months (from January 2013 on) simultaneously at the five cities, these were analysed for the contents of OC, EC, anions, cations, major and trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to these data sets in a harmonized way for each city. The sum of vehicle exhaust (VEX) and non-exhaust (NEX) contributes between 3.9 and 10.8 µg m−3 (16–32 %) to PM10 and 2.3 and 9.4 µg m−3 (15–36 %) to PM2.5, although a fraction of secondary nitrate is also traffic-related but could not be estimated. Important contributions arise from secondary particles (nitrate, sulfate and organics) in PM2.5 (37–82 %) but also in PM10 (40–71 %), mostly at background sites, revealing the importance of abating gaseous precursors in designing air quality plans. Biomass burning (BB) contributions vary widely, from 14–24 % of PM10 in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB, to  <  2 % in BCN-UB. In PM2.5, BB is the second most important source in MLN-UB (21 %) and in POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but is again negligible (< 2 %) in BCN-UB. This large variability among cities is mostly due to the degree of penetration of biomass for residential heating. In Barcelona natural gas is very well supplied across the city and is used as fuel in 96 % of homes, while in other cities, PM levels increase on an annual basis by 1–9 µg m−3 due to biomass burning influence. Other significant sources are the following. – Local dust, 7–12 % of PM10 at SUB and UB sites and 19 % at the TR site, revealing a contribution from road dust resuspension. In PM2.5 percentages decrease to 2–7 % at SUB-UB sites and 15 % at the TR site. – Industry, mainly metallurgy, contributing 4–11 % of PM10 (5–12 % in PM2.5), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial emissions was found in FI-UB and ATH-SUB. – Natural contributions from sea salt (13 % of PM10 in POR-TR, but only 2–7 % in the other cities) and Saharan dust (14 % in ATH-SUB, but less than 4 % in the other cities). During high pollution days, the largest sources (i.e. excluding secondary aerosol factors) of PM10 and PM2.5 are VEX + NEX in BCN-UB (27–22 %) and POR-TR (31–33 %), BB in FI-UB (30–33 %) and MLN-UB (35–26 %) and Saharan dust in ATH-SUB (52–45 %). During those days, there are also quite important industrial contributions in BCN-UB (17–18 %) and local dust in POR-TR (28–20 %).

scholarly journals AIRUSE-LIFE+: a harmonized PM speciation and source apportionment in 5 Southern European cities

2015 ◽  
Vol 15 (17) ◽  
pp. 23989-24039 ◽  
Author(s):  
F. Amato ◽  
A. Alastuey ◽  
A. Karanasiou ◽  
F. Lucarelli ◽  
S. Nava ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Urban Areas ◽  
The Other ◽  
Saharan Dust ◽  
Industrial Emissions ◽  
Urban Background ◽  
Large Variability ◽  
Pm10 And Pm2.5 ◽  
Local Dust

Abstract. The AIRUSE-LIFE+ project aims at characterising similarities and heterogeneities in PM sources and contributions in urban areas from the Southern Europe. Once the main PMx sources are identified, AIRUSE aims at developing and testing the efficiency of specific and non-specific measures to improve urban air quality. This article reports the results of the source apportionment of PM10 and PM2.5 conducted at three urban background sites (Barcelona, Florence and Milan, BCN-UB, FI-UB, MLN-UB) one sub-urban background site (Athens, ATH-SUB) and one traffic site (Porto, POR-TR). After collecting 1047 PM10 and 1116 PM2.5 24 h samples from January 2013 to February 2014 simultaneously at the 5 cities, these were analysed for the contents of OC, EC, anions, cations, major and trace elements and levoglucosan. The USEPA PMF5 receptor model was applied to these datasets in a harmonised way for each city. The sum of vehicle exhaust and non-exhaust contributes within 3.9–10.8 μg m−3 (16–32 %) to PM10 and 2.3–9.4 μg m−3 (15–36 %) to PM2.5, although a fraction of secondary nitrate is also traffic-related but could not be estimated. Important contributions arise from secondary particles (nitrate, sulphate and organics) in PM2.5 (37–82 %) but also in PM10 (40–71 %) mostly at background sites, revealing the importance of abating gaseous precursors in designing air quality plans. Biomass burning (BB) contributions vary widely, from 14–24 % of PM10 in POR-TR, MLN-UB and FI-UB, 7 % in ATH-SUB to < 2 % in BCN-UB. In PM2.5, BB is the second most important source in MLN-UB (21 %) and in POR-TR (18 %), the third one in FI-UB (21 %) and ATH-SUB (11 %), but again negligible (< 2 %) in BCN-UB. This large variability among cities is mostly due to the degree of penetration of biomass for residential heating. In Barcelona natural gas is very well supplied across the city and used as fuel in 96 % of homes, while, in other cities, PM levels increase on an annual basis by 1–9 μg m−3 due to this source. Other significant sources are: - Local dust, 7–12 % of PM10 at SUB and UB sites and 19 % at the TR site, revealing a contribution from road dust resuspension. In PM2.5 percentages decrease to 2–7 % at SUB-UB sites and 15 % at the TR site. - Industries, mainly metallurgy, contributing 4–11 % of PM10 (5–12 % in PM2.5), but only at BCN-UB, POR-TR and MLN-UB. No clear impact of industrial emissions was found in FI-UB and ATH-SUB. - Natural contributions from sea salt (13 % of PM10 in POR-TR but only 2–7 % in the other cities) and Saharan dust (14 % in ATH-SUB), but less than 4 % in the other cities. During high pollution days, the largest specific source (i.e. excluding SSO and SNI) of PM10 and PM2.5 are: VEX+NEX in BCN-UB (27–22 %) and POR-TR (31–33 %), BB in FI-UB (30–33 %) and MLN-UB (35–26 %) and Saharan dust in ATH-SUB (52–45 %) During those days, there are also quite important Industrial contributions in BCN-UB (17–18 %) and Local dust in POR-TR (28–20 %).

scholarly journals Spatial Distribution, Source Apportionment, Ozone Formation Potential, and Health Risks of Volatile Organic Compounds over a Typical Central Plain City in China

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1365
Author(s):  
Kun He ◽  
Zhenxing Shen ◽  
Jian Sun ◽  
Yali Lei ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Source Apportionment ◽  
Organic Compounds ◽  
Health Risks ◽  
Urban Areas ◽  
High Time Resolution ◽  
Ozone Formation ◽  
Industrial Site ◽  
Industrial Emissions ◽  
Volatile Organic

The profiles, contributions to ozone formation, and associated health risks of 56 volatile organic compounds (VOCs) species were investigated using high time resolution observations from photochemical assessment monitoring stations (PAMs) in Luoyang, China. The daily averaged concentration of total VOCs (TVOCs) was 21.66 ± 10.34 ppbv in urban areas, 14.45 ± 7.40 ppbv in suburbs, and 37.58 ± 13.99 ppbv in an industrial zone. Overall, the VOCs levels in these nine sites followed a decreasing sequence of alkanes > aromatics > alkenes > alkyne. Diurnal variations in VOCs exhibited two peaks at 8:00–9:00 and 19:00–20:00, with one valley at 23:00–24:00. Source apportionment indicated that vehicle and industrial emissions were the dominant sources of VOCs in urban and suburban sites. The industrial site displayed extreme levels, with contributions from petrochemical-related sources of up to 38.3%. Alkenes and aromatics displayed the highest ozone formation potentials because of their high photochemical reactivity. Cancer and noncancer risks in the industrial site were higher than those in the urban and suburban areas, and USEPA possible risk thresholds were reached in the industrial site, indicating PAMs VOC–related health problems cannot be ignored. Therefore, vehicle and industrial emissions should be prioritized when considering VOCs and O3 control strategies in Luoyang.

scholarly journals Chemical Composition and Source Apportionment of PM2.5 in Urban Areas of Xiangtan, Central South China

2019 ◽  
Vol 16 (4) ◽  
pp. 539 ◽  
Author(s):  
Xiaoyao Ma ◽  
Zhenghui Xiao ◽  
Lizhi He ◽  
Zongbo Shi ◽  
Yunjiang Cao ◽  
...  
Keyword(s):  
Source Apportionment ◽  
South China ◽  
Urban Areas ◽  
Inorganic Ions ◽  
Water Soluble ◽  
Total Carbon ◽  
Anthropogenic Sources ◽  
Vehicle Exhaust ◽  
Industrial Emissions ◽  
Wind Speeds

Xiangtan, South China, is characterized by year-round high relative humidity and very low wind speeds. To assess levels of PM2.5, daily samples were collected from 2016 to 2017 at two urban sites. The mass concentrations of PM2.5 were in the range of 30–217 µg/m3, with the highest concentrations in winter and the lowest in spring. Major water-soluble ions (WSIIs) and total carbon (TC) accounted for 58–59% and 21–24% of the PM2.5 mass, respectively. Secondary inorganic ions (SO42−, NO3−, and NH4+) dominated the WSIIs and accounted for 73% and 74% at the two sites. The concentrations of K, Fe, Al, Sb, Ca, Zn, Mg, Pb, Ba, As, and Mn in the PM2.5 at the two sites were higher than 40 ng/m3, and decreased in the order of winter > autumn > spring. Enrichment factor analysis indicates that Co, Cu, Zn, As, Se, Cd, Sb, Tl, and Pb mainly originates from anthropogenic sources. Source apportionment analysis showed that secondary inorganic aerosols, vehicle exhaust, coal combustion and secondary aerosols, fugitive dust, industrial emissions, steel industry are the major sources of PM2.5, contributing 25–27%, 21–22%, 19–21%, 16–18%, 6–9%, and 8–9% to PM2.5 mass.

scholarly journals Sources of organic aerosols in Europe: a modeling study using CAMx with modified volatility basis set scheme

2019 ◽  
Vol 19 (24) ◽  
pp. 15247-15270 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Agricultural Waste ◽  
Organic Aerosols ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

scholarly journals The impact of biomass burning and aqueous-phase processing on air quality: a multi-year source apportionment study in the Po Valley, Italy

2019 ◽  
Author(s):  
Marco Paglione ◽  
Stefania Gilardoni ◽  
Matteo Rinaldi ◽  
Stefano Decesari ◽  
Nicola Zanca ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Cold Season ◽  
World Health ◽  
Rural Site ◽  
Urban Site ◽  
Urban Background ◽  
Po Valley

Abstract. The Po Valley (Italy) is a well-known air quality hotspot characterized by Particulate Matter (PM) levels well above the limit set by the European Air Quality Directive and by the World Health Organization, especially during the colder season. In the framework of the Emilia-Romagna regional project SUPERSITO, the southern Po Valley submicron aerosol chemical composition was characterized by means of High-Resolution Aerosol Mass Spectroscopy (HR-AMS) with the specific aim of organic aerosol (OA) characterization and source apportionment. Eight intensive observation periods (IOPs) were carried out over four years (from 2011 to 2014) at two different sites (Bologna, BO, urban background and San Pietro Capofiume, SPC, rural background), to characterize the spatial variability and seasonality of the OA sources, with a special focus on the cold season. On the multi-year basis of the study, the AMS observations show that OA accounts for an average 45 ± 8 % (ranging 33–58 %) and 46 ± 7 % (ranging 36–50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and at the rural site, respectively. Primary organic aerosol (POA) comprises biomass burning (23 ± 13 % of OA) and fossil fuel (12 ± 7 %) contributions with a marked seasonality in concentration. As expected, the biomass burning contribution to POA is more significant at the rural site (urban/rural concentrations ratio of 0.67), but it is also an important source of POA at the urban site during the cold season, with contributions ranging from 14 to 38 % of the total OA mass. Secondary organic aerosol (SOA) contribute to OA mass to a much larger extent than POA at both sites throughout the year (69 ± 16 % and 83 ± 16 % at urban and rural, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning ageing products during the cold season, even at the urban background site. This biomass burning SOA fraction represents 14–44 % of the total OA mass in the cold season, indicating that in this region a major contribution of combustion sources to PM mass is mediated by environmental conditions and atmospheric reactivity. Among the environmental factors controlling the formation of SOA in the Po Valley, the availability of liquid water in the aerosol was shown to play a key role in the cold season. We estimate that organic fraction originating from aqueous reactions of biomass burning products (bb-aqSOA) represents 21 % (14–28 %) and 25 % (14–35 %) of the total OA mass and 44 % (32–56 %) and 61 % (21–100 %) of the SOA mass at the urban and rural sites, respectively.

scholarly journals Exploration of PM<sub>2.5</sub> sources on the regional scale in the Pearl River Delta based on ME-2 modeling

2018 ◽  
Vol 18 (16) ◽  
pp. 11563-11580 ◽  
Author(s):  
Xiao-Feng Huang ◽  
Bei-Bing Zou ◽  
Ling-Yan He ◽  
Min Hu ◽  
André S. H. Prévôt ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Pollution Control ◽  
Pearl River Delta ◽  
Regional Scale ◽  
Pearl River ◽  
Industrial Emissions ◽  
Annual Average ◽  
The Pearl River Delta ◽  
The Pearl River

Abstract. The Pearl River Delta (PRD) of China, which has a population of more than 58 million people, is one of the largest agglomerations of cities in the world and had severe PM2.5 pollution at the beginning of this century. Due to the implementation of strong pollution control in recent decades, PM2.5 in the PRD has continuously decreased to relatively lower levels in China. To comprehensively understand the current PM2.5 sources in the PRD to support future air pollution control strategies in similar regions, we performed regional-scale PM2.5 field observations coupled with a state-of-the-art source apportionment model at six sites in four seasons in 2015. The regional annual average PM2.5 concentration based on the 4-month sampling was determined to be 37 µg m−3, which is still more than 3 times the WHO standard, with organic matter (36.9 %) and SO42- (23.6 %) as the most abundant species. A novel multilinear engine (ME-2) model was first applied to a comprehensive PM2.5 chemical dataset to perform source apportionment with predetermined constraints, producing more environmentally meaningful results compared to those obtained using traditional positive matrix factorization (PMF) modeling. The regional annual average PM2.5 source structure in the PRD was retrieved to be secondary sulfate (21 %), vehicle emissions (14 %), industrial emissions (13 %), secondary nitrate (11 %), biomass burning (11 %), secondary organic aerosol (SOA, 7 %), coal burning (6 %), fugitive dust (5 %), ship emissions (3 %) and aged sea salt (2 %). Analyzing the spatial distribution of PM2.5 sources under different weather conditions clearly identified the central PRD area as the key emission area for SO2, NOx, coal burning, biomass burning, industrial emissions and vehicle emissions. It was further estimated that under the polluted northerly air flow in winter, local emissions in the central PRD area accounted for approximately 45 % of the total PM2.5, with secondary nitrate and biomass burning being most abundant; in contrast, the regional transport from outside the PRD accounted for more than half of PM2.5, with secondary sulfate representing the most abundant transported species.

scholarly journals A DECADAL ANALYSIS AND SENSITIVITY STUDY USING MOPITT CO COLUMNS OVER ASIA

2018 ◽  
Vol XLII-3/W5 ◽  
pp. 53-59 ◽  
Author(s):  
C. Lin ◽  
J. Cohen
Keyword(s):  
Standard Deviation ◽  
Biomass Burning ◽  
Urban Areas ◽  
Sensitivity Study ◽  
The Other ◽  
Peak Time ◽  
Urban Regions ◽  
Forest Clearing ◽  
Other Hand ◽  
A New Technique

<p><strong>Abstract.</strong> Biomass burning and urbanization are both significant sources of CO emissions and atmospheric loadings in the real environment. The sources of CO are due to incomplete combustion, on one hand of biomass from agriculture or forest clearing, and on the other hand from coal, oil, gas, and other similar materials. However, the spatial and temporal underlying properties and patterns are quite different between these two types of source regions, with urban regions having a relatively constant source of CO emissions, with only short term concentration fluctuations due to local meteorology. On the other hand, in biomass burning regions, the emissions themselves tend to be highly concentrated over a short burning period, and very low otherwise. We hence present a new technique to classify and quantify biomass burning regions and urban regions based on an objective analysis of the CO total column measurements from the MOPITT satellite. By using all of the data from 2000&amp;ndash;2016, in connection with averages and standard deviation cutoffs, we successfully determine these regions. By performing a sensitivity analysis, in connection with additional ground-based measurements, we determine that the ideal cutoffs for the mean column loading and standard deviation of the column loading 28<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>1017<span class="thinspace"></span>mol/cm<sup>2</sup> and 6<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>1017<span class="thinspace"></span>mol/cm<sup>2</sup> respectively. These results are capable of representing known urban regions and biomass burning regions well throughout China, Southeast Asia, and South Asia, specifically including Beijing, Hebei, Shandong, Jiangsu, Anhui, Hunan, Guangdong, and Bangkok on one hand, and Northeastern India, Myanmar, Laos, Northern Thailand, and Vietnam on the other hand. A detailed analysis of the time series over the different classified regions show that while the urban areas have a much higher annual value, and a relatively long peak time, that their maximum is never as high as the peaks in the biomass burning regions, and that these peaks in the biomass burning regions are extremely short in duration, although they occur annually or bi-annually. Finally, we have not been able to obtain a statistically relevant decreasing trend, as others have found, making CO possibly an interesting species for future studies.</p>

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

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 121 ◽  
Author(s):  
Jun Hu ◽  
Han Wang ◽  
Jingqiao Zhang ◽  
Meng Zhang ◽  
Hefeng Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Urban Areas ◽  
Emission Control ◽  
Clean Energy ◽  
Ambient Air ◽  
Control Measures ◽  
Ambient Air Quality ◽  
Surrounding Areas ◽  
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.

scholarly journals The impact of biomass burning and aqueous-phase processing on air quality: a multi-year source apportionment study in the Po Valley, Italy

2020 ◽  
Vol 20 (3) ◽  
pp. 1233-1254 ◽  
Author(s):  
Marco Paglione ◽  
Stefania Gilardoni ◽  
Matteo Rinaldi ◽  
Stefano Decesari ◽  
Nicola Zanca ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Cold Season ◽  
Rural Site ◽  
Urban Site ◽  
Urban Background ◽  
Po Valley ◽  
Rural Sites

Abstract. The Po Valley (Italy) is a well-known air quality hotspot characterized by particulate matter (PM) levels well above the limit set by the European Air Quality Directive and by the World Health Organization, especially during the colder season. In the framework of Emilia-Romagna regional project “Supersito”, the southern Po Valley submicron aerosol chemical composition was characterized by means of high-resolution aerosol mass spectroscopy (HR-AMS) with the specific aim of organic aerosol (OA) characterization and source apportionment. Eight intensive observation periods (IOPs) were carried out over 4 years (from 2011 to 2014) at two different sites (Bologna, BO, urban background, and San Pietro Capofiume, SPC, rural background), to characterize the spatial variability and seasonality of the OA sources, with a special focus on the cold season. On the multi-year basis of the study, the AMS observations show that OA accounts for averages of 45±8 % (ranging from 33 % to 58 %) and 46±7 % (ranging from 36 % to 50 %) of the total non-refractory submicron particle mass (PM1-NR) at the urban and rural sites, respectively. Primary organic aerosol (POA) comprises biomass burning (23±13 % of OA) and fossil fuel (12±7 %) contributions with a marked seasonality in concentration. As expected, the biomass burning contribution to POA is more significant at the rural site (urban / rural concentration ratio of 0.67), but it is also an important source of POA at the urban site during the cold season, with contributions ranging from 14 % to 38 % of the total OA mass. Secondary organic aerosol (SOA) contributes to OA mass to a much larger extent than POA at both sites throughout the year (69±16 % and 83±16 % at the urban and rural sites, respectively), with important implications for public health. Within the secondary fraction of OA, the measurements highlight the importance of biomass burning aging products during the cold season, even at the urban background site. This biomass burning SOA fraction represents 14 %–44 % of the total OA mass in the cold season, indicating that in this region a major contribution of combustion sources to PM mass is mediated by environmental conditions and atmospheric reactivity. Among the environmental factors controlling the formation of SOA in the Po Valley, the availability of liquid water in the aerosol was shown to play a key role in the cold season. We estimate that the organic fraction originating from aqueous reactions of biomass burning products (“bb-aqSOA”) represents 21 % (14 %–28 %) and 25 % (14 %–35 %) of the total OA mass and 44 % (32 %–56 %) and 61 % (21 %–100 %) of the SOA mass at the urban and rural sites, respectively.

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