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Proceeding Paper

Developing a System for Integrated Environmental Information in Urban Areas: An Estimation of the Impact of Thermal Stress on Health †

by
Dimitrios Melas
1,
Daphne Parliari
1,*,
Theo Economou
2,
Christos Giannaros
3,
Natalia Liora
1,
Sophia Papadogiannaki
1,
Serafeim Kontos
1,
Stavros Cheristanidis
1,
Donatella Occhiuto
4,
Maria Agostina Frezzini
4,
Jonilda Kushta
2,
Theodoros Christoudias
2,
Chrysanthos Savvides
5,
Ioannis Christofides
5,
Giampietro Casasanta
6,
Stefania Argentini
6,
Athina Progiou
7,
George Papastergios
8 and
Apostolos Kelessis
8
1
Laboratory of Atmospheric Physics, School of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2
Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, 2121 Nicosia, Cyprus
3
Department of Physics, National and Kapodistrian University of Athens, 15784 Athens, Greece
4
ARPA Lazio, Regional Environmental Protection Agency, 00187 Rome, Italy
5
Department of Labour Inspection, Ministry of Labour and Social Insurance, 1080 Nicosia, Cyprus
6
Institute of Atmospheric Science and Climate, National Research Council, 00133 Rome, Italy
7
AXON ENVIRO-GROUP Ltd., 11257 Athens, Greece
8
Department of Operational Planning (Resilience Office), Municipality of Thessaloniki, 54636 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Presented at the 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023, Athens, Greece, 25–29 September 2023.
Published: 29 August 2023

Abstract

:
Poor air quality remains the largest environmental health risk in Europe, despite the EU policy efforts. Especially in cities, the synergistic interactions between the urban heat island and urban pollution result in premature mortality, associated with cardiovascular and respiratory diseases. Mediterranean urban areas are particularly susceptible under the consideration that the intensity, frequency, and duration of heat waves will increase due to climate change. The LIFE SIRIUS project designates that air quality management needs to go beyond traditional approaches in order to consider synergistic effects. This paper assesses the impact of temperature on daily mortality from 2004 to 2019 in the Republic of Cyprus with the use of a Generalized Additive Model (GAM). The association between mean daily temperature and mortality is nonlinear, implying that a prompt rise in deaths occurs when temperatures are high, while for colder temperatures, the effect is delayed. We report an inverted J-shaped relationship between mean temperature and mortality, with the most prominent effects on human health documented at low temperatures. The population under study appears to be acclimatized to local conditions, as mortality increases after 10 days of exposure to the environmental risk. The results of this study will assist in the definition of city-specific thresholds above which health warnings for the protection of the local population will be issued, in the framework of LIFE SIRIUS.

1. Introduction

The problem of poor air quality is becoming increasingly urgent, with cities around the world experiencing more frequent and severe episodes of high pollution levels [1], while the number of associated deaths is constantly increasing [2]. The detrimental effects of air pollution on human health are established, and there is a substantial body of evidence linking exposure to air pollution to increasing mortality especially from cardiovascular and respiratory causes [3,4,5], exacerbated chronic diseases [6], elevated mortality risk concerning frail inhabitants [7], and additional years of life lost [8].
Urban areas are particularly sensitive, because of the synergistic interactions between urban heat islands (UHIs) and urban pollution islands (UPIs). The UPI has been recently coined to describe the spatial and temporal variations in pollution concentrations that exist not only between urban and rural areas, but also within cities themselves [9]. This new term draws an analogy to UHI, which traditionally denotes the additional warmth in cities compared to their non-urbanized surroundings, as well as the thermal differences within urban areas [10]. The synergies between UHIs and UPIs become even more important when considering the increasing frequency, intensity, and duration of heat waves due to climate change [11]. Thus, air quality management in urban areas needs to go beyond the traditional approaches in order to consider the compound effects of UPIs, UHI, and heat waves.
Despite the implementation of EU policies for mitigating air pollution, numerous regions continue to exceed the recommended guidelines outlined in the European Council Directive 2008/50/EC. For instance, Thessaloniki, Greece, reported numerous exceedances in EU daily limits of PM10 for 2019 [12]. In the same year, Nicosia, Cyprus, documented violations not only for PM10, but for O3 thresholds as well [13], and Rome, Italy, surpassed the 2019 annual NO2 average [14]. The inability of national authorities to adhere to the PM10 and NO2 limits established by the EU in Thessaloniki and Rome, respectively, has resulted in the initiation of infringement proceedings by the European Commission against Italy (Case C-573/19 (https://curia.europa.eu/juris/document/document.jsf?text=&docid=217525&pageIndex=0&doclang=EN&mode=req&dir=&occ=first&part=1&cid=26708984 (accessed on 23 May 2023))) and in the recent conviction of Greece (Case C-70/21 (https://curia.europa.eu/juris/document/document.jsf?text=&docid=271781&pageIndex=0&doclang=EL&mode=req&dir=&occ=first&part=1&cid=5755193) (accessed on 23 May 2023)).
As a result, the European Court of Auditors proclaimed that EU countries are not protecting public health effectively, partly due to the inadequate performance of Air Quality Plans (AQPs) in ensuring compliance with European air quality standards [15].
In light of this, the project LIFE SIRIUS aims to enhance air quality planning in three EU urban metropolitan areas (Thessaloniki in Greece, Rome in Italy, and Nicosia in Cyprus) in order to
  • Assess and improve the cities’ air quality plans, considering current (2019) and future (2030) climate conditions;
  • Identify UHI and UPI hotspots and forthcoming HWs, where short-term mitigation measures should be prioritized;
  • Provide health-related warnings considering the differential heat and air pollutants’ effects through the examination of the air-pollution–mortality association at different temperature strata.
To set the scientific basis for the health-related warning systems of Nicosia, the assessment of premature mortality from short-term exposure to heat stress is realized. The present epidemiological study quantifies the impact of mean temperature on the human health of the population of Cyprus, and, secondly, it defines city-specific thresholds for issuing warnings for the protection of the population.

2. Materials and Methods

2.1. Study Area

This study focused on Cyprus, an island in the Eastern Mediterranean. Its climate is typical of the region, characterized by dry and warm summers (June–September) and variably “wet” winters (November–March). Autumn and spring are generally short-lived and transitions are sharp. During hot months, the temperature often reaches 36 °C. The specific study area (for which health data are available) is the area controlled by the Republic of Cyprus, an area inhabited by a population of about 1 million.

2.2. Data Analysis

We applied a distributed-lag non-linear model using the framework of Generalized Additive Models or GAMs ([16], ch. 7) in order to estimate the health impact of thermal stress by demonstrating temperature-related mortality effects in Cyprus.
The dataset, including the daily number of deaths and mean daily temperature (Tmean) between 2004 and 2019, was acquired from the Ministry of Health of the Republic of Cyprus. Specifically, the data comprise deaths from cardiovascular and respiratory causes (ICD10 codes I00–I99 and J00–J99). All post-processing analysis of model data was conducted via the mgcv package [17] within the statistical environment R [18].

3. Results and Discussion

Figure 1 displays the bi-dimensional exposure–lag-response surface of the estimated Relative Risk (RR) in a three-dimensional diagram for mean temperature and lag values. The risk values are relative to the overall (sample) mean mortality count during the period. The association between Tmean and mortality RR suggests an immediate increase in mortality for exposure to elevated temperatures, whereas for low ones, the effect is delayed, in agreement with the literature [19,20]. The impact on health is most prominent at very high values of the exposure variable at days 0–1, corresponding to an estimated increase in mortality of about 11%. The secondary peak of RR at low temperatures (5% mortality increase) indicates that the local population is vulnerable not only to heat but to cold as well.
To better understand this complex association, we extracted two-dimensional relationships: Figure 2 shows the overall cumulative exposure–response curve interpreted as the mean number of daily deaths cumulated over the entire lag period of 20 days, and Figure 3 illustrates the non-linear effects of Tmean on the mean number of daily deaths for each lag.
The exposure–response curve (Figure 2) is inversely J-shaped with the largest increase in mortality occurring at cold temperatures. The lowest point of the curve (25 °C) corresponds to the optimum temperature for the local population. In general, U, J, or V-shaped relationships between temperature and mortality have been identified in many previous studies (e.g., [21]), while the exact shape of the curve varies by geographic location, climatic, and demographic characteristics [22].
The estimated lag–response relationship (Figure 3) denotes the acclimatization of the Cyprus population to meteorological conditions of the region as mortality risk starts from the lowest point at day 0 and peaks 10 days later. The subsequent decrease (days 10–15) before the second peak (day 18) may be attributed to mortality displacement, which describes a negative risk in mortality followed by an event of extreme temperatures [23].

4. Conclusions

This study analyzes the impact of mean daily temperature on all-cause mortality of the population of Cyprus over a lag period of 20 days. Our findings indicate a rapid rise in mortality risk due to exposure to high temperatures, whereas for lower temperatures, the impact persists longer. Although local citizens appear to be acclimatized, the majority of deaths occur under cold conditions. The present results highlight the importance of implementing location-specific protection measures and offer significant insights for national and regional authorities to create effective health and air quality strategies.

Author Contributions

Conceptualization, D.M., D.P. and T.E.; methodology, D.M., D.P., and T.E.; software, D.P. and T.E.; validation, D.P. and S.K.; writing—original draft preparation, D.M. and D.P.; writing—review and editing, D.M., D.P., T.E., J.K., S.K., C.G., N.L., S.P., S.C., D.O., M.A.F., T.C., C.S., I.C., G.C., S.A., A.P., G.P., A.K.; visualization, D.P.; supervision, D.M.; project administration, D.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financed by the LIFE Programme of the European Union in the framework of the project LIFE21-GIE-EL-LIFE-SIRIUS/101074365.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Mortality data provided by the Ministry of Health of the Republic of Cyprus are confidential.

Acknowledgments

Daphne Parliari acknowledges the support provided by Greece and the European Union (European Social Fund-ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the Act “Enhancing Human Resources Research Potential by undertaking a Doctoral Research” Sub-action 2: «IKY Scholarship Programme for PhD candidates in the Greek Universities». The Cyprus Institute acknowledges support by the Horizon 2020 EMME-CARE project (grant no. 856612). Christos Giannaros acknowledges the support provided by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “3d Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project acronym: HEAT-ALARM; Project Number: 06885).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. European Environmental Agency. Air Quality in Europe—2020 Report; European Environmental Agency: Copenhagen, Denmark, 2020.
  2. WHO. Ambient Air Pollution: A Global Assessment of Exposure and Burden of Disease; WHO: Geneva, Switzerland, 2016. [Google Scholar]
  3. Analitis, A.; Katsouyanni, K.; Dimakopoulou, K.; Samoli, E.; Nikoloulopoulos, A.K.; Petasakis, Y.; Touloumi, G.; Schwartz, J.; Anderson, H.R.; Cambra, K.; et al. Short-term effects of ambient particles on cardiovascular and respiratory mortality. Epidemiology 2006, 17, 230–233. [Google Scholar] [CrossRef] [PubMed]
  4. Khaniabadi, Y.O.; Goudarzi, G.; Daryanoosh, S.M.; Borgini, A.; Tittarelli, A.; De Marco, A. Exposure to PM10, NO2, and O3 and impacts on human health. Environ. Sci. Pollut. Res. 2017, 24, 2781–2789. [Google Scholar] [CrossRef] [PubMed]
  5. Shao, M.; Yu, L.; Xiao, C.; Deng, J.; Yang, H.; Xu, W.; Chen, Y.; Liu, X.; Ni, J.; Pan, F. Short-term effects of ambient temperature and pollutants on the mortality of respiratory diseases: A time-series analysis in Hefei, China. Ecotoxicol. Environ. Saf. 2021, 215, 112160. [Google Scholar] [CrossRef] [PubMed]
  6. European Environmental Agency. Air Quality in Europe—2019 Report; European Environmental Agency: Copenhagen, Denmark, 2019.
  7. Parliari, D.; Giannaros, C.; Papadogiannaki, S.; Melas, D. Short-Term Effects of Air Pollution on Mortality in the Urban Area of Thessaloniki, Greece. Sustainability 2023, 15, 5305. [Google Scholar] [CrossRef]
  8. Orellano, P.; Reynoso, J.; Quaranta, N.; Bardach, A.; Ciapponi, A. Short-term exposure to particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) and all-cause and cause-specific mortality: Systematic review and meta-analysis. Environ. Int. 2020, 142, 105876. [Google Scholar] [CrossRef] [PubMed]
  9. Ulpiani, G. On the linkage between urban heat island and urban pollution island: Three-decade literature review towards a conceptual framework. Sci. Total Environ. 2021, 751, 141727. [Google Scholar] [CrossRef] [PubMed]
  10. Stewart, I.D.; Oke, T.R.; Krayenhoff, E.S. Evaluation of the “local climate zone” scheme using temperature observations and model simulations. Int. J. Climatol. 2014, 34, 1062–1080. [Google Scholar] [CrossRef]
  11. Intergovernmental Panel on Climate Change(IPCC). Climate Change 2021: The Physical Science Basis. Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. 2021. Available online: https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_TS.pdf (accessed on 23 May 2022).
  12. Ministry of Environment and Energy. Annual Report on Air Quality 2019; Ministry of Environment and Energy: Athens, Greece, 2020.
  13. Ministry of Labour, Welfare and Social Insurance. Annual Technical Report Air Quality 2019; Ministry of Labour, Welfare and Social Insurance: Nicosia, Cyprus, 2020.
  14. ARPA Lazio. Valutazione Della Qualita’ Dell’aria Della Regione Lazio 2019; ARPA Lazio: Rome, Italy, 2020. [Google Scholar]
  15. Air Pollution—Our Health is Still not Sufficiently Protected; Special Report No. 23/2018; European Court of Auditors: Luxembourg, 2018.
  16. Wood, S. Generalized Additive Models: An Introduction with R, 2nd ed.; Chapman and Hall/CRC: New York, NY, USA, 2017. [Google Scholar]
  17. Wood, S.N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. Ser. B Stat. Methodol. 2011, 73, 3–36. [Google Scholar] [CrossRef]
  18. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022; Available online: https://www.r-project.org/ (accessed on 9 May 2023).
  19. Parliari, D.; Cheristanidis, S.; Giannaros, C.; Keppas, S.C.; Papadogiannaki, S.; De’Donato, F.; Sarras, C.; Melas, D. Short-Term Effects of Apparent Temperature on Cause-Specific Mortality in the Urban Area of Thessaloniki, Greece. Atmosphere 2022, 13, 852. [Google Scholar] [CrossRef]
  20. Lubczy, J.; Christophi, C.A.; Lelieveld, J. Heat-related cardiovascular mortality risk in Cyprus: A case-crossover study using a distributed lag non-linear model. Environ. Health 2015, 14, 39. [Google Scholar] [CrossRef]
  21. Ma, W.; Chen, R.; Kan, H. Temperature-related mortality in 17 large Chinese cities: How heat and cold affect mortality in China. Environ. Res. 2014, 134, 127–133. [Google Scholar] [CrossRef] [PubMed]
  22. Nordio, F.; Zanobetti, A.; Colicino, E.; Kloog, I.; Schwartz, J. Changing patterns of the temperature-mortality association by time and location in the US, and implications for climate change. Environ. Int. 2015, 81, 80–86. [Google Scholar] [CrossRef] [PubMed]
  23. Baccini, M.; Biggeri, A.; Accetta, G.; Kosatsky, T.; Katsouyanni, K.; Analitis, A.; Anderson, H.R.; Bisanti, L.; D’Iippoliti, D.; Danova, J.; et al. Heat effects on mortality in 15 European cities. Epidemiology 2008, 19, 711–719. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Exposure-lag-response risk surface demonstrating the nonlinear association between mean temperature and mortality.
Figure 1. Exposure-lag-response risk surface demonstrating the nonlinear association between mean temperature and mortality.
Environsciproc 26 00117 g001
Figure 2. Cumulative exposure–response curve between daily Tmean and mortality over lag days 0–20.
Figure 2. Cumulative exposure–response curve between daily Tmean and mortality over lag days 0–20.
Environsciproc 26 00117 g002
Figure 3. Non-linear effects of Tmean on daily mortality at lag 0–20.
Figure 3. Non-linear effects of Tmean on daily mortality at lag 0–20.
Environsciproc 26 00117 g003
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MDPI and ACS Style

Melas, D.; Parliari, D.; Economou, T.; Giannaros, C.; Liora, N.; Papadogiannaki, S.; Kontos, S.; Cheristanidis, S.; Occhiuto, D.; Frezzini, M.A.; et al. Developing a System for Integrated Environmental Information in Urban Areas: An Estimation of the Impact of Thermal Stress on Health. Environ. Sci. Proc. 2023, 26, 117. https://0-doi-org.brum.beds.ac.uk/10.3390/environsciproc2023026117

AMA Style

Melas D, Parliari D, Economou T, Giannaros C, Liora N, Papadogiannaki S, Kontos S, Cheristanidis S, Occhiuto D, Frezzini MA, et al. Developing a System for Integrated Environmental Information in Urban Areas: An Estimation of the Impact of Thermal Stress on Health. Environmental Sciences Proceedings. 2023; 26(1):117. https://0-doi-org.brum.beds.ac.uk/10.3390/environsciproc2023026117

Chicago/Turabian Style

Melas, Dimitrios, Daphne Parliari, Theo Economou, Christos Giannaros, Natalia Liora, Sophia Papadogiannaki, Serafeim Kontos, Stavros Cheristanidis, Donatella Occhiuto, Maria Agostina Frezzini, and et al. 2023. "Developing a System for Integrated Environmental Information in Urban Areas: An Estimation of the Impact of Thermal Stress on Health" Environmental Sciences Proceedings 26, no. 1: 117. https://0-doi-org.brum.beds.ac.uk/10.3390/environsciproc2023026117

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