Long-term concentrations of fine particulate matter and impact on human health in Verona, Italy

Accepted Manuscript Long-term concentrations of fine particulate matter and impact on human health in Verona, Italy A. Pozzer, S. Bacer, S. De Zolt Sappadina, F. Predicatori, A. Caleffi PII:

S1309-1042(18)30346-5

DOI:

https://doi.org/10.1016/j.apr.2018.11.012

Reference:

APR 474

To appear in:

Atmospheric Pollution Research

Received Date: 14 June 2018 Revised Date:

25 October 2018

Accepted Date: 23 November 2018

Please cite this article as: Pozzer, A., Bacer, S., Sappadina, S.D.Z., Predicatori, F., Caleffi, A., Longterm concentrations of fine particulate matter and impact on human health in Verona, Italy, Atmospheric Pollution Research (2018), doi: https://doi.org/10.1016/j.apr.2018.11.012. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Long-term concentrations of fine particulate matter and impact on human health in Verona, Italy A.Pozzera , S.Bacera , S.De Zolt Sappadinab , F.Predicatorib , A.Caleffia Planck Institute for Chemistry, 55128, Mainz, Germany b ARPAV, via Dominutti, 37135, Verona, Italy

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Abstract

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Verona is an Italian city which experiences low levels of air quality due to its location near the centre of the Po Valley, one of the most polluted areas in Italy and in Europe. High pollutant concentrations, in particular of fine aerosol particles, are associated with detrimental effects on human health. The present study analyses the ground-based measurements of particulate matter with a diameter ≤ 2.5 µm (PM2.5 ) and ≤ 10 µm (PM10 ) registered in Verona and its province since 2002 to 2015. The annual means and the number of days when the European standards were exceeded show that air quality has slightly improved in the period 2002– 2015, with statistically significant negative trends present in both PM10 and PM2.5 levels. The annual mortality due to different diseases attributable to PM2.5 has been estimated for the period 2009–2014 by employing concentration-response functions based on epidemiological cohort studies. Results show that, on average, about 299 deaths per year (3 are infants) are caused by PM2.5 related diseases in Verona province. Among these, about 88 deaths per year (1 is infant) occur in Verona municipality. This means that 11.3% of the total deaths due to diseases of the respiratory and cardiovascular systems is attributable to long-term exposure to PM2.5 pollution. Keywords: Verona, PM2.5 measurements, air quality, health impact 1. Introduction

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The Po Valley is one of the most important industrial and agricultural areas in Italy and also in Europe. Air pollution in this region is relatively high compared to other European regions (Chu et al., 2003; Van Donkelaar et al., 2010), due to the industrialization and the high density of population (about 355 people/km2 nowadays). Additionally, the peculiar orography of the Po Valley, which is surrounded by the Alpine and Apennine chains for three-quarters, causes a scarce ventilation of the area so that stagnation of pollutants in the air is quite common, especially in fall-winter seasons (Giulianelli et al., 2014). The Po Valley counts about 20 million inhabitants and is now considered to be a large megacity, ranging from Turin (North-West of Italy) to Trieste (North-East of Italy) (Lawrence et al., 2007). Verona is a city of the Veneto region and lays almost in the centre of the Po Valley. The number of inhabitants is approximately 257,000 in the municipal city and about 922,000 in the whole provincial territory (ISTAT, 2018). According to local authorities (AMAT, Agenzia Mobilit`a Ambiente e Territorio) and the official emission database for Verona province (Veneto, 2013), air pollution in Verona is mostly produced by traffic (80%), followed by residential energy consumption (i.e. small combustion sources, especially for heating and cooking), and on a smaller level by industrial activities. Several source apportionment studies concerning the Po Valley area have confirmed the role of vehicular traffic and residential heating as the main local sources of fine particulate matter (Khan, 2016; Bigi and Ghermandi, 2016; Masiol et al., 2012). Verona suffers from Preprint submitted to Atmospheric Pollution Research

low air quality (Legambiente, 2018), as the air quality standards for fine particle matters are often exceeded, even twice as much as what enforced by the European Commission. It is well known that exposure to ambient air pollution (AAP) increases the incidence of a wide range of diseases (e.g. respiratory and cardiovascular diseases and cancer), with both long and short-term health effects (Shiraiwa et al., 2017; Pope III and Dockery, 2006; Lippmann et al., 2013; Burnett et al., 2014; Beelen et al., 2014). Pollution has been estimated to represent worldwide a significant fraction of the total mortality attributable to 26 risk factors assessed by the World Health Organization (WHO) Global Burden of Disease project (GBD). Heart disease and stroke are the most common reasons of death attributable to AAP and are in total responsible for 80% of premature deaths, followed by pulmonary diseases and lung cancer (WHO, 2014). The GBD of 2010 indicates that outdoor air pollution in the form of fine particulate matter (PM) is a much more significant public health risk than previously assumed (Lim et al., 2012). PM with a diameter smaller than 2.5 µm (PM2.5 ) and 10 µm (PM10 ) originates primarily from combustion sources (the former) and by mechanical processes, e.g. construction activities, road dust re-suspension, and wind (the latter). Ground-level concentrations of PM have been widely used to estimate air quality levels, and an intensive observational network has been established in Europe in the last 20 years. PM has been directly connected to the human health impact and has been estimated as the single largest environmental health risk in Europe (EEA, 2015). The health effects may vary by individual health or age and are predominantly associated to November 24, 2018

ACCEPTED MANUSCRIPT the respiratory and cardiovascular systems (WHO, 2005). Air pollution as a whole and PM as a separate component of air pollution mixtures have recently been classified as carcinogenic to humans by the specialized Agency for Research on Cancer (IARC) of the WHO (IARC, 2013). Epidemiological cohort studies have estimated the health effects of PM2.5 in a variety of geographical (mainly urban) locations, principally in USA, but also in Europe and specifically Italy (Michelozzi et al., 1998; Rossi et al., 1999, e.g.). Many estimations of air pollution attributable mortality exists in the literature. Evans et al. (2013) used a concentration-response function for the association between long-term PM2.5 exposure and mortality to calculate the lung cancer, cardiopulmonary disease, and ischemic heart disease mortality. Lelieveld et al. (2013) applied an epidemiological health impact function to compute cardiovascular disease and lung cancer mortality attributable to PM2.5 pollution in 2005, and Lelieveld et al. (2015) estimated that in Italy there were 20,809 premature deaths due to PM2.5 and ozone associated diseases in the year 2010. In the present study we analyse the concentrations of PM2.5 and PM10 measured from some ground-based stations located in the territory of Verona municipality and province since 2002 to 2015. The mortality attributable to PM2.5 related diseases is estimated for the period 2009–2014 using the concentrationresponse functions of Burnett et al. (2014). The paper is organised as follows: Section 2 describes the data used for this study and the method applied to the mortality estimation, in Section 3 we analyse the long series of PM2.5 and PM10 concentrations measured in Verona, in Section 4 we estimate the mortality attributable to PM2.5 pollution, finally, our conclusions are given in Section 5.

Bosco Chiesanuova

Fumane Corso Milano

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Giarol Grande Cason San Bonifacio San Giacomo

Legnago

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Bovolone

2. Data and methods

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Figure 1: Map of Verona province with the PM ground stations of ARPAV. The grey area depicts the territory of Verona municipality.

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2.1. PM measurements We used the measurements of PM2.5 and PM10 concentrations taken routinely by ARPAV (Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto) at different ground stations located in Verona municipality (Cason, Corso Milano, Giarol Grande, and via San Giacomo) and in Verona province (Bovolone, Bosco Chiesanuova, Fumane, Legnago, and San Bonifacio), shown in Figure 1. The stations are categorised in different typologies (traffic, industrial, background) and according to the zone of their location (urban, suburban, rural), following the criteria by Larssen et al. (1999); the categories for each station are shown in Table 1. These stations have been operative for different time spans, starting on 3rd January 2002. In this work we examined the data until 31st December 2015. The frequency of the measurements is once per day in Cason, Corso Milano, Giarol Grande, via San Giacomo, Bosco Chiesanuova, and San Bonifacio, while every two hours in Legnago, Fumane, and Bovolone. All the stations measured PM10 concentration, and only the station in Cason measured also PM2.5 starting from the 8th May 2007 (hereafter this station is referred to as “CasonPM25” when we deal with PM2.5 measurements). The stations use the principle of absorption of β radiation to calculate the value of PM with an automatic instrumentation.

However, this method is regularly tested using a gravimetric method at (50 ± 5)% relative humidity and (20 ± 1)◦C temperature. The difference between the two methods is less than 10 µg/m3 , with a sensitivity of 0.1 µg/m3 and a reproducibility equal to ±1 µg/m3 . For the analysis we employed the daily means computed with the measurements collected by the stations listed in Table 1. Bosco Chiesanuova was excluded being located in the mountain region (1,106 m altitude) so that it cannot be representative for the PM concentrations in the provincial territory. The measurements taken in via San Giacomo (in 2002, 2003, and 2004) and Giarol Grande (in 2015) were not considered as well since they never overlap with the measurements taken in Cason (necessary condition for the analysis in Section 3). The Corso Milano station was moved crosswise to the street by roughly 50 m at the end of 2007. Nevertheless, the NOx concentrations measured in the new location have showed that the station is still largely influenced by traffic, whereas a ∼10% decrease in PM10 has been estimated. Finally the Cason station has been moved at the end of 2015, therefore not influencing our reults. Table 1 shows also the period and the number of days per year when the stations were operative. 2.2. Population and mortality data Information about number of inhabitants and causes of death is obtained by the Italian National Institute of Statistics (ISTAT, 2018). We considered the annual data of “population resident on 1st January” in Verona municipality and Verona province within the period 2009–2014 and took into account the age categories “total” (all ages), “adults” (> 30 years) and “infants” (< 5 years). The total population resident in the province (Figure 2, top) increases by 1.5% from 2009 (908,492) to 2014 (921,717) and presents a slight positive trend. The number of adults also rises (by 2.6%) from 634,316 to 650,598, while the number of infants is characterised by a bell shape with a peak in 2011 (46,636). On the contrary, Verona municipality (Figure 2,

2

ACCEPTED MANUSCRIPT Type

Bovolone

Bs

Cason*

Bu

Corso Milano*

Tu

Fumane

Is

Legnago

Bu

San Bonifacio

Tu

CasonPM25

Bu

Number of available data 2002

213

2003

352

2004

2005

2006

2007

2008

2009 165

331

350

91

286

353

334

356

347

359

356

357

360

298

324

349

337

333

345

308

348

354

57

356

361

357

360

360 88

344

354

357

153

351

320

341

361

343

334

354

329

349

340

319

365

344

204

343

2010

2011

2012

2013

2014

2015

359

359

337

355

361

364

361

362

323

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Stations

SC

Table 1: List of the PM ground stations of ARPAV considered in this study (1st column), typologies of the stations (2nd column), and number of data (daily means) available for each year (other columns). The stations are classified as: T=traffic, I=industrial, B=background, u=urban, s=suburban, r=rural. The stations labelled with “*” are situated within the territory of Verona municipality, while the others are located in Verona province.

bottom) shows a slight negative trend both for the total population and the adults (more evident) determined by the big drop in 2012, while the number of infants oscillates around 11,000. Long-term exposure to PM2.5 is associated with increased mortality (Pope III and Dockery, 2006; Lippmann et al., 2013; Burnett et al., 2014; Beelen et al., 2014) from ischemic heart disease (IHD), cerebrovascular disease (CEV or stroke), chronic obstructive pulmonary disease (COPD), and lung cancer (LC) in adults, and from increased incidence of acute lower respiratory infections (ALRI) in infants. Thus, we considered from the ISTAT archive the number of deaths caused by these diseases in the territory of Verona province within the period 2009–2014 (mortality causes are not available beyond the year 2014 at the time of writing). In particular, ALRI has been computed as sum of three diseases classified as “pneumonia”, “influenza”, and “other diseases of the respiratory system” (Figure 3).

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Population in Verona province < 5 years

50000

Population (<5 years)

48000

850000

46000

800000 750000

44000

700000

42000 650000 2009

2010

2011

Years

2012

2013

2014

40000

Population in Verona municipality All ages >= 30 years

< 5 years

12000 11750

260000 11500

Population (<5 years)

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All ages >= 30 years

900000

600000

Population (All ages and >= 30 years)

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We computed the annual mortality attributable due to longterm exposure to PM2.5 using the concentration-response functions developed by Burnett et al. (2014). These functions relate changes in pollutant concentration to changes in mortality and are estimated by fitting an integrated exposure-response (IER) model with the available literature information. The IER coefficients (organized in bins of 1 µg/m3 ) are used to estimate the attributable fraction (AF) to air pollution of the mortality due to IHD, CEV, COPD, LC in adults, and ALRI in infants, following the approach used in Lelieveld et al. (2015). In this study the coefficients for the IER model are the ones of the GBD 2010 (Lim et al., 2012). These coefficients have been updated in the GBD 2015 (Forouzanfar et al., 2016), but they present an age-class differentiation which was not possible to achieve with the available population data. Higher mortalities attributable to air pollution are expected if the newer coefficients are be used. Therefore the mortalities estimated in this studies should be considered as a lower limit the mortalities estimated in this studies should be considered as a lower limit.. The annual averages of PM2.5 from the observations in Cason (representative for Verona province, as explained in Section

Population (All ages and >= 30 years)

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2.3. Mortality estimation

950000

11250

240000

11000 220000

10750 10500

200000

10250 180000

2009

2010

2011

Years

2012

2013

2014

10000

Figure 2: Yearly population registered as total, adult, and infantile resident in Verona province (top) and Verona municipality (bottom). Note the different vertical axes for total population and adults, left, and for infants, right

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ACCEPTED MANUSCRIPT Mortality in Verona province 2500

1000

2000

Total mortality

800

IHD CEV COPD LC ALRI Tot

1500 600

1000

400

500

200 0

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Mortality per different diseases

1200

2009

2010

2011

Years

2012

2013

2014

correspond to Cason and Corso Milano, the two stations within the municipal territory, and indicate a net decrease of PM10 with means mostly below the annual standard since 2008. A common feature of all profiles is a high peak (almost 50 µg/m3 for three stations) in 2011 and a low peak (below 32 µg/m3 for all stations) in 2014. Thus, there is a general tendency of PM10 to decrease since 2011, although meteorological factors (like rain, wind, inversions) play an important role in the pollutant dispersion. We note that the station in San Bonifacio is always characterised by higher means with respect to the other stations between 2011 and 2015, due to its peculiar location close to local sources such as highways and a smelter, and the PM10 levels in Corso Milano strongly reduce since 2007, the same year when the station was relocated. The relative trends shown in Figure 4 (middle) are in line with the results of Masiol et al. (2017) and Bigi and Ghermandi (2016), who estimated a yearly trend in the region within the range ∼ −(2–6)% for both PM10 and PM2.5 Additionally, we computed the ratio of the number of days per year when the PM10 daily European standard (i.e. 50µg/m3 ) has been exceeded adn the number of measurements available for the same year (Figure 4, bottom). In Table 2 the exceedances for each year and for each stations are also summarised. We observe that, although the trends are negative (apart in Bovolone), the yearly exceedances of the European standard are always above the threshold of 35 days per year within the period 20022015. The only exception is Fumane, which exceeded the European standard less than 35 days per year since 2014. It must be mentioned that in 2014 a cement plant in the area was closed down, changing the air quality in the surroundings (Predicatori et al., 2009). In summary, although an improvement in air quality is indeed present for the last decade, this is not enough to comply with the European Directive. PM2.5 measurements are collected for 9 years (2007–2015) only at the CasonPM25 station. Due to a change in the instrumentation characteristics at the end of 2008, only the years 2009–2015 are used in this work. The daily means of PM2.5 (Figure 5) show a great variability (with some values higher than 100 µg/m3 every year) which is dominated by the annual cycle. We computed the regression using the curve fitting method recommended by NOAA for time series (Thoning et al., 1989) which filters and smooths the data in order to investigate the signal in the record without the influence by local sources and sinks. Following this method we obtain a negative slope (−0.463 ± 0.027) which confirms our previous results and the decreasing trend in this region. It has been shown that the PM2.5 decrease is a general feature in all the greater Po Valley area and not specifically in the Verona province. In fact, the estimated trend of PM2.5 is in line with the ones observed in many other stations in the region (Bigi and Ghermandi, 2016, see Tab.2) and “[..] was generated by the renewal in vehicular fleet over the Po Valley, i.e. the introduction of vehicles having more efficient engines and improved emission control systems” (Bigi and Ghermandi, 2016), rather than a local political action aimed to improve air quality. Further, the economical crisis started in 2008 could also have contributed in reducing PM2.5 , as many industries shut down and the heavy traffic was reduced

0

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Figure 3: Yearly mortality for IHD, CEV, COPD, LC, and infant ALRI in Verona province between 2009 and 2014. The total mortality is also depicted (note the different vertical axes for the mortality for each disease left, and for the total mortality, right).

3.2) were used in the IER model. The mortality attributable to PM2.5 pollution was then estimated according to the function: Mort = y0 · AF · Pop

(1)

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where Mort is the annual mortality attributable to air pollution, Pop is the adult (> 30 year) or infant (< 5 years) population exposed to the pollutants in a certain area (i.e. Verona municipality and Verona province), and y0 is the baseline mortality rate (BMR) for a given population and a specific disease. BMR is the ratio of the mortality due to a certain natural health problem over the population and is usually computed for each range of age. As mortality data are available only for the total population in Verona province, here BMR is not differentiated between adults and infants but refers to the total population in the provincial territory. The uncertainty associated to the mortality estimation is determined by the error of the instruments measuring PM2.5 concentrations (i.e ±1 µg/m3 ) and the uncertainties of the AF (population and mortality data are supposed not to be affected by errors). We used the lower and upper bounds of AF to calculate a minimum and maximum mortality via eq. (1), as AF is the main source of errors. 3. PM2.5 and PM10 concentrations

3.1. Long-term concentrations and trends of PM10 and PM2.5 According to the European Commission, which establishes health based standards for different air pollutants present in the air, the annual and the daily means of PM10 concentration cannot exceed 40 µg/m3 and 50 µg/m3 more than 35 days per year, respectively, while the PM2.5 annual European standard is 25 µg/m3 . Figure 4 (top) shows the annual means of PM levels registered in Verona between 2002 and 2015 by the stations listed in Table 1, with the condition that the number of daily averages each year has to be higher than 200. The longest series 4

ACCEPTED MANUSCRIPT (ACI, 2018). The annual means of PM2.5 (Figure 4, top) oscillate between 21 µg/m3 (in 2013 and 2014) and 28 µg/m3 (in 2011) exceeding the annual standard in 2009, 2011, and 2015. Concluding, air quality in Verona is not only not satisfying the European Commission guidelines, but is also very far to meet the WHO air quality guideline, i.e. 20 µg/m3 and 10 µg/m3 as annual means of PM10 and PM2.5 (WHO, 2005). Nevertheless, it must also be stressed that WHO claimed that “no threshold has been identified below which no damage to health is observed [..], and therefore the guidelines are aimed to achieve the lowest concentration possible” (WHO, 2005).

Annual means of PM2.5 and PM10 Bovolone Cason* (-1.165±0.441) g/m3yr 1 Corso Milano* (-2.744±0.440) g/m3yr 1 Fumane (-1.502±0.398) g/m3yr 1 Legnago (1.240±2.868) g/m3yr 1 San Bonifacio (-1.192±1.546) g/m3yr 1 CasonPM25* (-0.454±0.481) g/m3yr 1

70

50 40 30 20

In Figure 6, the fit and correlation between PM10 measured in Cason and the other stations in the province are shown. We observe that PM10 concentrations in Bovolone tend to be higher than the levels in Cason, the opposite occurs in Fumane, Legnago, and San Bonifacio (where the slopes are lower than 1), while the slope between the two stations in Verona municipality (Cason and Corso Milano) is very close to the unity. The coefficients of determination (R2 ) of the least-squares regressions indicate that the PM10 ground-based stations have a strong linear relationship which explains 65%−75% of the total variation of the data. This suggests that the PM10 concentrations measured in Cason are representative for all the provincial territory of Verona. Further, as shown in Figure 6f, a robust linear relationship (R2 = 88%) is found between the PM10 and PM2.5 measured in Cason, proving that PM10 variations are well linearly represented by PM2.5 data. This indicates that PM2.5 is a dominant contributor to PM10 in this region, confirming the findings of Masiol et al. (2015), Marcazzan et al. (2003), and Bigi and Ghermandi (2016). It is hence reasonable to assume that the PM2.5 concentrations measured in Cason are representative for the PM2.5 concentrations in the entire province. This confirms the finding of Bigi and Ghermandi (2016) and Masiol et al. (2017), who showed a low PM2.5 concentration variability within the stations in the Po Valley area of the Veneto region.

2002

2004

2006

2008

2010

Years

2012

SC

3.2. Regional representativeness of PM2.5

RI PT

PM [ g/m3]

60

2014

Annual means variations in PM2.5 and PM10 50 40

PM variations [%]

M AN U

30

Bovolone Cason* (-3.22±1.22)%yr 1 Corso Milano* (-4.85±0.78)%yr 1 Fumane (-4.39±1.16)%yr 1 Legnago (3.57±8.26)%yr 1 San Bonifacio (-3.23±4.19)%yr 1 CasonPM25* (-1.71±1.81)%yr 1

20 10

0

10 20 30 40

4. Health effects

2006

2008

Years

2010

2012

2014

Bovolone (11.06±6.86)%yr 1 Cason* (-1.83±0.62)%yr 1 Corso Milano* (-3.42±0.57)%yr 1 Fumane (-1.52±0.32)%yr 1 Legnago (-7.68±5.69)%yr 1 San Bonifacio (-1.76±1.27)%yr 1 CasonPM25* (-0.49±1.12)%yr 1

70 60 50 40 30 20 10 0 2002

By using the health impact function (eq. 1) we computed the yearly mortality by IHD, CEV, COPD, and LC for adults, and ALRI for infants, as well as the corresponding uncertainties, both in Verona municipality and in Verona province (Figure 7). It must be stressed that the data of the Verona municipality are included in the calculations of the Verona province. The period of analysis is limited to 2009–2014 because PM2.5 measurements are not provided (or not homogeneous) before 2009, while mortality data are not available beyond 2014. We observe in Figure 7 (top) that, within the provincial territory, the highest cause of mortality attributable to air pollution is IHD (134 yearly deaths on average between 2009 and 2014 with the 95% confidence level between 94 and 184, i.e. 134:94–184), followed by CEV (103:39–165). The number of

2004

Exceedances of European standards # exceedances /# available data [%]

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50 2002

2004

2006

2008

Years

2010

2012

2014

Figure 4: (Top): Annual means of PM10 concentrations in Verona municipality and province (continuous lines) and annual means of PM2.5 measured at the CasonPM25 station (red dashed line). The yellow areas highlight the annual standards enforced by the European Commission: 40 µg/m3 for PM10 and 25 µg/m3 for PM2.5 . (Middle): Relative annual means of PM with respect to the first year with available observations (i.e. (PMyear /PMyear−start − 1) · 100) for each station. (Bottom): Ratios between exceedances of 50 µg/m3 and yearly available data of PM10 daily averages (continuous lines) and between exceedances of 25 µg/m3 and yearly available data of PM2.5 daily averages (red dashed line). The yellow area indicates the allowed number of exceedances (35/365 · 100) for PM10 from the European air quality standard. Inside the boxes, the slope coefficients and the corresponding standard errors are shown for temporal series longer than three years.

5

ACCEPTED MANUSCRIPT Exceedances of the European standard

Stations

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

62

131

131

127

82

57

82

121

62

80

52

68

50

146

205

191

130

88

12

57

92

69

129

104

55

54

56

49 41

70

48

83

San Bonifacio

41

80

108

94

73

36

77

CasonPM25

29

29

42

32

23

18

33

Bovolone Cason* Corso Milano*

104

214

Fumane

2013

2014

2015

62

40

83

79

43

65

48

16

27

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Legnago

2012

Table 2: Exceedances of the European standard, i.e. number of daily mean concentrations higher than 50 µg/m3 every year, for both PM10 and PM2.5 .

Temporal series of PM2.5

SC

140

3. However, the minimum and maximum mortality estimations highlight the large uncertainty which affects the results preventing from the detection of a statistically significant trend.

y = -0.463x +26.248 = 0.027

120

5. Conclusions

80 60 40 20 0 2009

2010

2011

2012

2013

Years

2014

2015

M AN U

PM2.5 [ g/m3]

100

2016

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Figure 5: Temporal series of PM2.5 daily means (blue dots) and fit computed via the NOAA method (green line).

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yearly deaths due to LC and COPD are 43:10–68 and 17:6–27, respectively, while the mean of yearly infantile deaths is 3:2– 4. We find that, on average, 11.3% (i.e. 299:151–448 yearly deaths) of the total yearly deaths due to diseases of the respiratory and cardiovascular systems during the period 2009–2014 is attributable to PM2.5 . The impact of PM2.5 for each disease, on average, is: 13.8% for IHD, 16.9% for CEV, 9.5% for LC, 7.6% for COPD, and 0.7% for ALRI (Figure. 8). We observe that all mortality estimates present a negative trend in the period 2009–2014, more pronounced for IHD and CEV, however, these trends are not significant given the large uncertainties associated to the AFs. A common feature is a local minimum in 2010 and an absolute minimum in 2014, analogously with the PM2.5 observations (see Figure 4). Changes in mortality attributable to PM2.5 in Verona municipality (Figure 7, bottom) are very similar to the ones of the province. Between 2009 and 2014 there are on average 40:28– 54 deaths due to IHD, 30:11–49 due to CEV, 13:3–20 due to of LC, 5:2–8 for COPD, and 1:0–1 for ALRI, which means an average of 88:44–132 yearly deaths due to diseases of the respiratory and cardiovascular systems attributable to PM2.5 . In general, we find that the total mortality attributable to PM2.5 presents a slight tendency to decrease (Figure 9) which is related to the negative trend of PM2.5 computed in Section

6

We have analysed the concentrations of PM2.5 and PM10 measured from ground-based stations located in the territory of Verona municipality and province between 2002 and 2015. We found that, although PM10 annual means decreased in the period, the concentrations are still elevated, often exceeding the annual and the daily European standards. The measurements of PM2.5 collected at the CasonPM25 station show a small (statistically significant) negative trend in the period 2009–2015, but the annual means are anyway alarming, close to or higher than the annual European standard of 25 µg/m3 . It must be further stressed that the decrease observed in PM2.5 is due to a regular update in the vehicle fleet and it is not caused by the intervention of local or regional authorities or by long-term-measures aimed to improve significantly air quality in the region (Bigi and Ghermandi, 2016). With the assumption that the PM2.5 measurements collected in Cason are representative for the entire provincial territory, we have estimated the mortality attributable to PM2.5 related diseases (IHD, CEV, COPD, LC for adults, and ALRI for infants) between 2009 and 2014 using the concentration-response functions of Burnett et al. (2014). We found that in Verona province, on average for the period 2009–2014, 11.3% (i.e. 299:151–448 deaths) of the total yearly deaths due to diseases of the respiratory and cardiovascular systems are attributable to PM2.5 . The highest cause of mortality attributable to air pollution is IHD (about 134 yearly deaths), followed by CEV (about 103 yearly deaths). Still in 2014, mortality associated to PM2.5 pollution in the province of Verona is very high with 253:129–379 yearly deaths. Due to the strong uncertainties, it is not possible to extrapolate a significant trend in mortality attributable to air pollution. Nevertheless, thanks to improvements in technology, a decrease in the vehicular emissions (main player in the region) should be expected, associated with an even stronger decrease in mortality, due to the non linearity of the response of human health to pollutants exposure.

ACCEPTED MANUSCRIPT

175

150

150

150

125

125

100

75

75

50

50

y = 1.204x +3.645 R2 = 0.753

0

0

225

25

50

75

0

Cason*

50

y = 1.080x +4.224 R2 = 0.752

0

225

(d)

200

75

25

100 125 150 175 200 225

100

25

50

75

0

100 125 150 175 200 225 Cason*

150

125

125

100 75

50 25 0

25

50

75

Cason*

0

50

y = 0.962x +7.562 R2 = 0.652

25

100 125 150 175 200 225

100 75

50

y = 0.888x +5.687 R2 = 0.651

50

0

25

50

75

100 125 150 175 200 225 Cason*

y = 1.115x +6.307 R2 = 0.878

25

100 125 150 175 200 225 Cason*

75

M AN U

75

0

Cason*

175

150 San Bonifacio

175

25

(f)

200

150

100

0

225

175

125

y = 0.756x +4.247 R2 = 0.726

25

(e)

200

RI PT

100

Fumane

175

125

(c)

200

175

25

Legnago

225

(b)

200

Corso Milano*

Bovolone

225

(a)

200

SC

225

0

0

25

50

75

100 125 150 175 200 225

CasonPM25*

Figure 6: Linear regressions and coefficients of determination (R2 ) computed with daily means of PM10 in Cason and the other five stations (a, b, c, d, e) and with daily means of PM2.5 and PM10 measured in Cason (f ).

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Mortality attributable to PM2.5 in Verona province CEV 175 125

2010

2012

Years

2014

25 0

y = -7.348x +128.636 R2 = 0.839

2010

Mort

2012

Years

20

20

40

0

2014

y = -2.613x +48.685 R2 = 0.916

2010

2012

Years

5 0

y = -0.199x +17.393 R2 = 0.035

2010

CEV

3

40

2

20

1

0

0

2012

Years

2014

2010

COPD

50

8

40

6

2012

Years

2014

y = -0.057x +3.018 R2 = 0.093

2010

2014

10 0

4

y = -2.471x +39.056 R2 = 0.880

2010

2012

Years

LC 25

2014

2 0

y = -0.107x +5.296 R2 = 0.113

2010

2012

Years

2014

0.8 0.6

10

0.4

5

0.2

0

0.0

2012

Years

2014

1.0

15

2010

2012

Years

ALRI

y = -0.711x +15.236 R2 = 0.933

20

30

10

60

Mortality attributable to PM2.5 in Verona municipality

30

50

4

10

IHD 60

ALRI

y = -1.976x +50.094 R2 = 0.906

80

15

EP

50 y = -7.523x +160.216 R2 = 0.875

LC

20

100 75

COPD

30 25

150

AC C

Mort

IHD 200 175 150 125 100 75 50 25 0

2014

y = -0.019x +0.751 R2 = 0.198

2010

2012

Years

2014

Figure 7: Annual mortality by IHD, CEV, COPD, and LC in adults, and ALRI in infants associated to PM2.5 exposure, both in Verona province (top) and in Verona municipality (bottom), and the corresponding uncertainties.

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ACCEPTED MANUSCRIPT Mortality attributable to PM2.5 in % IHD (-0.22±0.11)%yr 1 CEV (-0.85±0.38)%yr 1 COPD (-0.22±0.13)%yr 1 LC (-0.28±0.17)%yr 1 ALRI (-0.05±0.02)%yr 1 TOT (-0.49±0.17)%yr 1

25

15 10

RI PT

Mort in %

20

5 0 2009

2010

2011

Years

2012

2013

N.J., Krewski, D., 2013. Estimates of global mortality attributable to particulate air pollution using satellite imagery. Environmental Research 120, 33–42. doi:https://doi.org/10.1016/j.envres.2012.08.005. Forouzanfar, M.H., Afshin, A., Alexander, L.T., Anderson, H.R., Bhutta, Z.A., Biryukov, S., Brauer, M., Burnett, R., Cercy, K., Charlson, F.J., et al., 2016. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the global burden of disease study 2015. The Lancet 388, 1659–1724. Giulianelli, L., Gilardoni, S., Tarozzi, L., Rinaldi, M., Decesari, S., Carbone, C., Facchini, M., Fuzzi, S., 2014. Fog occurrence and chemical composition in the po valley over the last twenty years. Atmospheric Environment 98, 394–401. doi:https://doi.org/10.1016/j.atmosenv.2014.08.080. IARC, 2013. IARC: Outdoor air pollution a leading environmental cause of cancer deaths. Technical Report. International Agency for Research on Cancer (IARC). ISTAT, 2018. Istituto nazionale di statistica. URL: http://www.istat.it. Khan, M.B., 2016. Inorganic and organic pollutants in atmospheric aerosols: chemical composition and source apportionment . Larssen, S., Sluyter, R., Helmis, C., 1999. Criteria for EOROAIRNET: The EEA Air Quality Monitoring and Information Network. European Environment Agency. Lawrence, M.G., Butler, T.M., Steinkamp, J., Gurjar, B.R., Lelieveld, J., 2007. Regional pollution potentials of megacities and other major population centers. Atmospheric Chemistry and Physics 7, 3969–3987. doi:10.5194/ acp-7-3969-2007. Legambiente, 2018. Legambiente. URL: http://www.legambiente.it. Lelieveld, J., Barlas, C., Giannadaki, D., Pozzer, A., 2013. Model calculated global, regional and megacity premature mortality due to air pollution. Atmospheric Chemistry and Physics 13, 7023–7037. URL: https://www.atmos-chem-phys.net/13/7023/2013/, doi:10. 5194/acp-13-7023-2013. Lelieveld, J., Evans, J., Fnais, M., Giannadaki, D., Pozzer, A., 2015. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525, 367–371. doi:10.1038/nature15371. Lim, S.S., T., V., Flaxman, A., Danaei, G., Shibiya, K., 2012. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the global burden of disease study 2010. Lancet 380, 2224–2260. Lippmann, M., Chen, L.C., Gordon, T., Ito, K., Thurston, G.D., 2013. National particle component toxicity (npact) initiative: integrated epidemiologic and toxicologic studies of the health effects of particulate matter components. Research Report (Health Effects Institute) , 5–13. Marcazzan, G., Ceriani, M., Valli, G., Vecchi, R., 2003. Source apportionment of pm10 and pm2. 5 in milan (italy) using receptor modelling. Science of the Total Environment 317, 137–147. Masiol, M., Benetello, F., Harrison, R.M., Formenton, G., De Gaspari, F., Pavoni, B., 2015. Spatial, seasonal trends and transboundary transport of pm2. 5 inorganic ions in the veneto region (northeastern italy). Atmospheric Environment 117, 19–31. Masiol, M., Squizzato, S., Ceccato, D., Rampazzo, G., Pavoni, B., 2012. Determining the influence of different atmospheric circulation patterns on pm10 chemical composition in a source apportionment study. Atmospheric environment 63, 117–124. Masiol, M., Squizzato, S., Formenton, G., Harrison, R.M., Agostinelli, C., 2017. Air quality across a european hotspot: Spatial gradients, seasonality, diurnal cycles and trends in the veneto region, ne italy. Science of The Total Environment 576, 210–224. Michelozzi, P., Forastiere, F., Fusco, D., Perucci, C., Ostro, B., Ancona, C., Pallotti, G., 1998. Air pollution and daily mortality in rome, italy. Occupational and Environmental Medicine 55, 605–610. Pope III, C.A., Dockery, D.W., 2006. Health effects of fine particulate air pollution: lines that connect. Journal of the air & waste management association 56, 709–742. Predicatori, F., Intini, B., Frontero, P., Martinelli, C., Culmone, L., Brunelli, S., Salomoni, A., Mosconi, C., Mattiolo, G., 2009. Influence of a cement industry on the fine and ultrafine particles composition in a rural area. Radiation protection dosimetry 137, 288–293. Rossi, G., Vigotti, M.A., Zanobetti, A., Repetto, F., Gianelle, V., Schwartz, J., 1999. Air pollution and cause-specific mortality in milan, italy, 1980–1989. Archives of Environmental Health: An International Journal 54, 158–164.

2014

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Figure 8: Mortalities attributable to long-term exposure to PM2.5 in comparison with the total mortality associated to IHD, CEV, COPRD, LC, and ALRI in Verona province.

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It is important to note that these results have to be considered as minimum values as the new concentration-response functions derived by Cohen et al. (2017) following the GBD 2015 are more sensitive to low levels of PM2.5 and generate attributable fractions higher than the ones used here: within the range 10 − 30 µg/m3 of PM2.5 the new AFs are bigger by a factor 2 for COPD and ALRI, and about a factor 1.5 for IHD (for people 45 years old). Concluding, this study wants to stress the high level of mortality attributable to PM2.5 in Verona and its province and underline the urgency to address the air pollution problem in the region.

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ACI, 2018. Automobile club d’italia. URL: http://www.aci.it. Beelen, R., Raaschou-Nielsen, O., Stafoggia, M., Andersen, Z.J., Weinmayr, G., Hoffmann, B., Wolf, K., Samoli, E., Fischer, P., Nieuwenhuijsen, M., et al., 2014. Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 european cohorts within the multicentre escape project. The Lancet 383, 785–795. Bigi, A., Ghermandi, G., 2016. Trends and variability of atmospheric pm 2.5 and pm 10–2.5 concentration in the po valley, italy. Atmospheric Chemistry and Physics 16, 15777–15788. Burnett, R.T., Pope III, C.A., Ezzati, M., Olives, C., Lim, S.S., Mehta, S., Shin, H.H., Singh, G., Hubbell, B., Brauer, M., Andreson, H.R., Smith, K.R., Balmes, J.R., Bruce, N.G., Kan, H., Laden, F., Pr¨uss-Ust¨un, A., Turner, M.C., Gapstur, S.M., Diver, W.R., Cohen, A., 2014. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental Health Perspectives 122, 397–403. doi:10.1289/ehp.1307049. Chu, D.A., Kaufman, Y., Zibordi, G., Chern, J., Mao, J., Li, C., Holben, B., 2003. Global monitoring of air pollution over land from the earth observing system-terra moderate resolution imaging spectroradiometer (modis). Journal of Geophysical Research: Atmospheres 108. Cohen, A.J., Brauer, M., Burnett, R., Anderson, H.R., Frostad, J., Estep, K., Balakrishnan, K., Brunekreef, B., Dandona, L., Dandona, R., Feigin, V., Freedman, G., Hubbell, B., Jobling, A., Kan, H., Knibbs, L., Liu, Y., Randall, M., Morawska, L., Pope III, C.A., Shin, H., Straif, K., Shaddick, G., Thomas, M., van Dingenen, R., von Donkelaar, A., Vos, T., Murray, C.J., Forouzanfar, M.H., 2017. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: An analysis of data from the global burden of diseases study 2015. Lancet 389, 1907–1918. EEA, 2015. Air quality in Europe : 2015 report. Technical Report. European Environmental Agency (EEA). Evans, J., van Donkelaar, A., Martin, R.V., Burnett, R., Rainham, D.G., Birkett,

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Mortality attributable to PM2.5 Verona municipality 140 120 100 80 60 40 20 0

Mort

400 300 200 100 0

y = -17.103x +359.356 R2 = 0.850

2009

2010

2011

2012

Years

2013

2014

RI PT

Verona province

500

y = -5.920x +109.024 R2 = 0.898

2009

2010

2011

2012

Years

2013

2014

SC

Figure 9: Annual total mortality associated to PM2.5 exposure for all ages, both in Verona province (left) and in Verona municipality (right), and the corresponding uncertainties.

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Shiraiwa, M., Ueda, K., Pozzer, A., Lammel, G., Kampf, C.J., Fushimi, A., Enami, S., Arangio, A.M., Frohlich-Nowoisky, J., Fujitani, Y., et al., 2017. Aerosol health effects from molecular to global scales. Environmental science & technology 51, 13545–13567. Thoning, K.W., Tans, P.P., Komhyr, W.D., 1989. Atmospheric carbon dioxide at mauna loa observatory: 2. analysis of the noaa gmcc data, 1974–1985. Journal of Geophysical Research: Atmospheres 94, 8549–8565. Van Donkelaar, A., Martin, R.V., Brauer, M., Kahn, R., Levy, R., Verduzco, C., Villeneuve, P.J., 2010. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environmental health perspectives 118, 847. Veneto, A.V.R., 2013. Inemar veneto 2013 - inventario regionale delle emissioni in atmosfera in regione veneto. URL: http://www.arpa. veneto.it/temi-ambientali/aria/emissioni-di-inquinanti/ inventario-emissioni. WHO, 2005. Air quality guidelines for particulate matter, ozone, nitrogen dioxide and sulfur dioxide. Global update 2005. Technical Report. World Health Organization (WHO). WHO, 2014. Burden of disease from Ambient Air Pollution for 2012. Technical Report. World Health Organization (WHO).

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Long-term concentrations of fine particulate matter and impact on human health in Verona, Italy

1 Max-Planck Institute of Chemistry, Mainz, Germany 2 ARPAV, Verona, Italy

Highlights

EP

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M AN U

SC

Observations of pm2.5 in Verona (Italy) are investigated for the period 2009-2014 Statistical significant negative trend is present for the period in the area The human health impact of fine particulate is estimated Air pollution has significant incidence on the mortality in the region

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• • • •

RI PT

A.Pozzer 1 , S.Bacer 1 , S.De Zolt 2 , F.Predicatori 2 , A. Caleffi 1