- Email: [email protected]
Analysis of traffic and industrial source contributions to ambient air pollution with nitrogen dioxide in two urban areas in Romania
Available online at www.sciencedirect.com
ScienceDirect ScienceDirect
Energy Procedia 00 (2018) 000–000 Available online www.sciencedirect.com Available online atatwww.sciencedirect.com Energy Procedia 00 (2018) 000–000
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www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia 157 Energy Procedia 00(2019) (2017)1553–1560 000–000 www.elsevier.com/locate/procedia
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18, Technologies and Materials for Renewable Energy, and Sustainability, TMREES18, 19–21 September 2018,Environment Athens, Greece 19–21 September 2018, Athens, Greece
Analysis of traffic and industrial source contributions to ambient air 15th International Symposium on District Heating and Cooling Analysis ofThe traffic and industrial to Romania ambient air pollution with nitrogen dioxidesource in twocontributions urban areas in pollution with nitrogen dioxide in two urban areas in Romania Assessing the using the Paraschiv heat demand-outdoor a Spirufeasibility Paraschiva*,of Lizica-Simona † a a Spiru Paraschiv *, Lizica-Simona Paraschiv †demand forecast temperature function for a long-term district heat “Dunarea de Jos” University of Galati, Domneasca street, no. 47, Romania a a
“Dunarea de Jos” University of Galati, Domneasca street, no. 47, Romania
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Abstract IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Environnement - IMT Atlantique, rue Alfred Kastler, 44300 Nantes, France The main purpose of this study is toÉnergétiques investigateetNO in two4 urban areas in Romania based on data measured 2 temporal distribution from traffic by stationary monitoring 2016 and Analysis of the measurement that NObased 2 emissions The main purpose of this stations study is during to investigate NO2017. distribution in two urbandata areasshow in Romania on data measured 2 temporal typestationary sources has a higher stations contribution to 2016 the urban pollution than industry type source.data Theshow analysis emission trendfrom in the two traffic by monitoring during and 2017. Analysis of the measurement thatofNO 2 emissions cities (for 2 years), shows contribution an effective reduction in emissions fromindustry industrial type sourceThe butanalysis an increase in emissions traffic type sources has a higher to the urban pollution than type source. of emission trendfrom in the two Abstract with 12.88 to 28.45 %. type citiessource (for 2 years), shows an effective reduction in emissions from industrial type source but an increase in emissions from traffic type source with 12.88 to 28.45 %. heating networks are commonly in the literature as one of the most effective solutions for decreasing the ©District 2018 The Authors. Published by Elsevier addressed Ltd. greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat © 2019 The Authors. Published by Elsevier Ltd. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. by Elsevier Ltd. This is an open access article under theconditions CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) sales. Due topeer-review the changed climate and building renovationofpolicies, heat demand in thefor future could decrease, Selection and under responsibility of the scientific committee Technologies and Materials Renewable Energy, This is an and openpeer-review access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, prolonging the investment return period. Environment and Sustainability, TMREES18. Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and of Sustainability, The main scope this paper is TMREES18. to assess the feasibility of using the heat demand – outdoor temperature function for heat demand Environment and Sustainability, TMREES18. forecast. Urban; The district of Alvalade, in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Keywords: Air pollution; Nitrogen located dioxide; Traffic emissions; Industrial emissions; buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Keywords: Urban; Air pollution; Nitrogen dioxide; Traffic emissions; Industrial emissions; renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were with results from a dynamic heat demand model, previously developed and validated by the authors. 1.compared Main text The results showed that when only weather change is considered, the margin of error could be acceptable for some applications 1. Main text (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation Air pollution and especially urban air pollution is an alarming phenomenon. Exposure to air pollutants can cause scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). Airvalue pollution andcoefficient especially urban aironpollution is an alarming to air pollutants can cause serious health problems, including respiratory problems (asthma, lung irritation, pneumonia, decreased The of slope increased average within the range phenomenon. of 3.8% up to Exposure 8%bronchitis, per decade, that corresponds to the serious health problems, including respiratory problems (asthma, lung irritation, bronchitis, pneumonia, decreased decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
* Corresponding author. Tel.: +40721320403. E-mail address:author. [email protected] * Corresponding Tel.: +40721320403. © 2017 The Authors. Published by Elsevier Ltd. * Corresponding Tel.: +40766255759. E-mail address:author. [email protected] Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and E-mail address:author. [email protected] * Corresponding Tel.: +40766255759. Cooling. E-mail address: [email protected] 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Keywords: Heat demand; Forecast; Climate change license (https://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access under the CC BY-NC-ND 1876-6102 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific of Technologies and Materials for Renewable Energy, Environment This is an open access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) and Sustainability, TMREES18. Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18. 10.1016/j.egypro.2018.11.321
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resistance to respiratory infections), allergies, cancer and even premature death. Even if significant progress has been made to reduce emissions from industrial sources with a substantial decrease in NO2 concentrations, road traffic has become the first source of emissions in urban areas. Also, authorities must take important decisions to determine people to use public transport or bicycles in order to reduce air pollution and its effects on health and environment hazardous. EURO standards have had a clear benefit in terms of reducing PM emissions from diesel cars, especially from EURO 5 and EURO 6, but not for reducing emissions of NO2. Furthermore, the proportion of diesel cars has increased significantly in many European cities due to the lower cost of diesel fuel, making it obviously the need for nontechnological measures aimed to reduce the use of private cars in cities to meet the pollutant concentration standards. The problem may be even worse in the major cities of Europe due to the higher number of inhabitants and car densities. 2. Measurement sites and techniques This study focuses on the interpretation of 2016-2017 trends for the NO2 concentration from traffic-urban and industrial spaces from two cities in Romania. The two analyzed cities, Galati and Braila, have approximately 430000 inhabitants. The analyzed data are from two traffic monitoring stations and two industrial stations one of each type for each city. Fig.1 provides information on the location of the analyzed areas.
Fig. 1. Location of the monitoring sites considered in this work
3. Results The evaluation of the NO2 concentration level for Braila highlighted the following temporal trends: - in 2016, between January and September, the concentration of NO2 at the traffic station was higher than that recorded at the industrial station; - between October and November, the NO2 concentration at the industrial station recorded a very sharp increase, followed by a decrease towards the end of the year as shown in the figure 2; - in 2017, the NO2 concentration had a similar trend, but the period of sharp increase was recorded for a period of about two times shorter according to Fig. 3;
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
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- this trend is probably due by the addition at the pollution generated in Braila of the pollution due to intensification of the pollutant transport by the wind from the steel plant located at a distance of 20 km. 250.00
NO2 [µg/m³]
200.00 150.00 100.00 50.00 0.00
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Hours (2016) BR‐4 ‐ industrial
BR‐1 ‐ traffic
Fig. 2. Hourly variation of NO2 concentration measured in Braila at traffic and industrial stations in 2016.
Annual NO2 pollution cycles indicate changes from month to month in the concentration of this pollutant (Fig. 4). The data presented in Fig. 4 are from processing of data provided by the National Air Quality Monitoring Network for Galati and Braila. 400.00 350.00
NO2 [µg/m³]
300.00 250.00 200.00 150.00 100.00 50.00 0.00
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Hours (2017) BR‐4 ‐ industrial
BR‐1 ‐ traffic
Fig. 3. Hourly variation of NO2 concentration measured in Braila at traffic and industrial stations in 2017.
NO2 pollution from traffic in Galati in winter was much more severe than in other seasons, with a maximum value of 93.09 μg / m3, followed by spring (77,33 μg / m3) and autumn (54.94 μg/m3) according to Fig. 5.
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
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120
NO2 [µg/m³]
100 80 60 40 20 1 276 551 826 1101 1376 1651 1926 2201 2476 2751 3026 3301 3576 3851 4126 4401 4676 4951 5226 5501 5776 6051 6326 6601 6876 7151 7426 7701 7976 8251 8526
0
Hours (2016) GL‐1 ‐ traffic
GL‐4 ‐ industrial
Fig. 4. Hourly variation of NO2 concentration measured in Galati at traffic and industrial stations in 2016.
NO2 [µg/m³]
100.00 80.00 60.00 40.00 20.00 1 276 551 826 1101 1376 1651 1926 2201 2476 2751 3026 3301 3576 3851 4126 4401 4676 4951 5226 5501 5776 6051 6326 6601 6876 7151 7426 7701 7976 8251 8526
0.00
Hours (2017) GL‐1 ‐ traffic
GL‐4 ‐ industrial
Fig. 5. Hourly variation of NO2 concentration measured in Galati at traffic and industrial stations in 2017.
During summer months, air pollution with NO2 is lower, but this may be due to higher photochemical air pollution, as there are favorable conditions to O3 production (high temperatures, strong ultraviolet radiation and light winds). Atmospheric pollution with NO2 is higher in winter due to more crowded traffic due to snow and other NO2 sources such as heating systems that increase background concentrations. The weekly cycle highlights daily emissions variations, mainly related to weekly human activities (working week / weekend). The daily cycle shows hour-by-hour changes in pollutant concentrations, this is influenced by traffic intensity and weather conditions that have a major influence on pollutant dispersion and transformation as shown in Fig. 8. From Fig. 6 and 7 it can be noticed that at the traffic station in Galati there are recorded maximum monthly values higher than those of the industrial station. It can be seen that the average monthly value at this type of station is also higher, the concentration being higher in the winter months and lower in the summer months.
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
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NO2 [µg/m³]
100.00 80.00 60.00 40.00 20.00 0.00
1
2
3
4
5
6
7
8
9
10
11
12
Month (2017) Fig. 6. Annual trends of mean, maximum and minimum values of NO2 at traffic station in 2017 for Galati
NO2 [µg/m³]
Fig. 6 shows the seasonal variation of the NO2 concentration in Galati at the traffic type station in 2017. We can see that the monthly mean concentrations of NO2 are highest in the winter months, probably reflecting the seasonal variation in the lifetime of NO2. 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00
1
2
3
4
5
6
7
8
9
10
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Month (2017) Fig. 7. Annual trends of mean, maximum and minimum values of NO2 at industrial station in 2017 for Galati
Fig. 6 and 7 show the mean seasonal differences between the NO2 concentrations measured on the same time intervals at the two types of stations. In winter, when the lifetime of NO2 is the longest, the average NO2 concentration is higher than in the summer, due to the shorter summer chemical lifetimes. Spring and autumn show diurnal variations between the winter and summer extremes. In winter, the NO2 concentration increase throughout the day as emissions are higher during the day than during the night. The weekly cycle of NO2 concentration in Galati for traffic and industrial stations is shown in Fig. 8 and 9 for period between January and December 2017. The weekly cycle highlights low concentrations of NO2 on Saturdays and Sundays, which correspond to the weekend pattern and the rest days. We notice significant reductions of NO2 concentration on Saturday and Sunday, with about 40% relative to the weekday mean. The diurnal variation of tropospheric NO2 concentration depends on the diurnal cycle of NO2 emissions and chemical transformations. In urban areas, the NO2 concentrations present maximum daytime values that mainly reflect the intense vehicles use early in the morning and late afternoon.
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Fig. 8. Daily hourly variation of NO2 concentrations at the BR-1 traffic station in 2016
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
Fig. 9. Daily hourly variation of NO2 concentrations at the BR-1 traffic station in 2017
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4. Conclusions In 2016 and 2017, at the traffic and industrial measurement type stations in Braila, the hourly average values for NO2 exceeded the European limit value of 40 μg / m3. The observed decrease in NO2 concentration at industrial monitoring stations agrees with the reduction of NO2 emissions from industry due to technology development for pollution reduction. However, the NO2 concentrations at these stations remained either increased and only a reduction of the primarily emitted NO2 due to improved emission control systems alone is not sufficient to reduce the NO2 concentrations significantly. However, the NO2 concentrations at these stations remained higher, and only a reduction of the NO2 emissions due to improved emission control systems alone is not sufficient to reduce the NO2 concentrations. References [1] Spiru Paraschiv, Daniel-Eduard Constantin, Simona-Lizica Paraschiv, Mirela Voiculescu, “OMI and Ground-Based In-Situ Tropospheric Nitrogen Dioxide Observations over Several Important European Cities during 2005–2014”, Int. J. Environ. Res. Public Health 14(11) (2017): 1415, doi:10.3390/ijerph14111415. [2] Anaïs Pasquier, Michel André, “Considering criteria related to spatial variabilities for the assessment of air pollution from traffic”, Transportation Research Procedia 25 (2017): 3354-3369, doi :10.1016/j.trpro.2017.05.210. [3] Sun Chanjuan, Zhang Jialing, Guo Yuchao, Fu Qingyan, Liu Wei, Pan Jun, Huang Yanmin, Zou Zhijun, Huang Chen, “Outdoor air pollution in relation to sick building syndrome (SBS) symptoms among residents in Shanghai, China”, Energy and Buildings 174 (2018): 68-76, doi :10.1016/j.enbuild.2018.06.005. [4] Maryam Shekarrizfard, Ahmadreza Faghih-Imani, Louis-Francois Tétreault, Shamsunnahar Yasmin, Frederic Reynaud, Patrick Morency, Celine Plante, Louis Drouin, Audrey Smargiassi, Naveen Eluru, Marianne Hatzopoulou, “Regional assessment of exposure to traffic-related air pollution: Impacts of individual mobility and transit investment scenarios”, Sustainable Cities and Society 29 (2017): 68-76, doi:10.1016/j.scs.2016.12.002 [5] Paraschiv Lizica-Simona, Paraschiv Spiru Ion V.Ion, “Increasing the energy efficiency of buildings by thermal insulation”, Energy Procedia 128 ( 2017): 393-399, doi:10.1016/j.egypro.2017.09.044. [6] Jean-Marie Cariolet, Morgane Colombert, Marc Vuillet, Youssef Diab, “Assessing the resilience of urban areas to traffic-related air pollution: Application in Greater Paris”, Science of The Total Environment 615 (2018): 588-596, doi:10.1016/j.scitotenv.2017.09.334 [7] Khaled Gasmi, Abdulaziz Aljalal, Watheq Al-Basheer, Mumin Abdulahi, “Analysis of NOx, NO and NO2 ambient levels in Dhahran, Saudi Arabia”, Urban Climate 21 (2017): 232-242, doi :10.1016/j.uclim.2017.07.002 [8] Paraschiv Spiru, Paraschiv Lizica-Simona, “A review on interactions between energy performance of the buildings, outdoor air pollution and the indoor air quality”, Energy Procedia 128 (2017): 179-186, doi:10.1016/j.egypro.2017.09.039. [9] Lizica-Simona. Paraschiv, Spiru Paraschiv, Ion V. Ion, Nicusor Vatachi, “Techno-economic Analysis of the Emissions Reduction Technologies in the Thermal Power Plants in Romania”, J Environ Prot Ecol, 14 (2) (2013): 770. [10] M. Istrate, A. Banica, “Recent dynamics of air pollution from thermal power plants – evidence from Romania, Bulgaria and Greece, Journal of Environmental Protection and Ecology 17, No 3, 831–839, 2016.
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Energy Procedia 157 Energy Procedia 00(2019) (2017)1553–1560 000–000 www.elsevier.com/locate/procedia
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18, Technologies and Materials for Renewable Energy, and Sustainability, TMREES18, 19–21 September 2018,Environment Athens, Greece 19–21 September 2018, Athens, Greece
Analysis of traffic and industrial source contributions to ambient air 15th International Symposium on District Heating and Cooling Analysis ofThe traffic and industrial to Romania ambient air pollution with nitrogen dioxidesource in twocontributions urban areas in pollution with nitrogen dioxide in two urban areas in Romania Assessing the using the Paraschiv heat demand-outdoor a Spirufeasibility Paraschiva*,of Lizica-Simona † a a Spiru Paraschiv *, Lizica-Simona Paraschiv †demand forecast temperature function for a long-term district heat “Dunarea de Jos” University of Galati, Domneasca street, no. 47, Romania a a
“Dunarea de Jos” University of Galati, Domneasca street, no. 47, Romania
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a Abstract IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Environnement - IMT Atlantique, rue Alfred Kastler, 44300 Nantes, France The main purpose of this study is toÉnergétiques investigateetNO in two4 urban areas in Romania based on data measured 2 temporal distribution from traffic by stationary monitoring 2016 and Analysis of the measurement that NObased 2 emissions The main purpose of this stations study is during to investigate NO2017. distribution in two urbandata areasshow in Romania on data measured 2 temporal typestationary sources has a higher stations contribution to 2016 the urban pollution than industry type source.data Theshow analysis emission trendfrom in the two traffic by monitoring during and 2017. Analysis of the measurement thatofNO 2 emissions cities (for 2 years), shows contribution an effective reduction in emissions fromindustry industrial type sourceThe butanalysis an increase in emissions traffic type sources has a higher to the urban pollution than type source. of emission trendfrom in the two Abstract with 12.88 to 28.45 %. type citiessource (for 2 years), shows an effective reduction in emissions from industrial type source but an increase in emissions from traffic type source with 12.88 to 28.45 %. heating networks are commonly in the literature as one of the most effective solutions for decreasing the ©District 2018 The Authors. Published by Elsevier addressed Ltd. greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat © 2019 The Authors. Published by Elsevier Ltd. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. by Elsevier Ltd. This is an open access article under theconditions CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) sales. Due topeer-review the changed climate and building renovationofpolicies, heat demand in thefor future could decrease, Selection and under responsibility of the scientific committee Technologies and Materials Renewable Energy, This is an and openpeer-review access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, prolonging the investment return period. Environment and Sustainability, TMREES18. Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and of Sustainability, The main scope this paper is TMREES18. to assess the feasibility of using the heat demand – outdoor temperature function for heat demand Environment and Sustainability, TMREES18. forecast. Urban; The district of Alvalade, in Lisbon (Portugal), was used as a case study. The district is consisted of 665 Keywords: Air pollution; Nitrogen located dioxide; Traffic emissions; Industrial emissions; buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district Keywords: Urban; Air pollution; Nitrogen dioxide; Traffic emissions; Industrial emissions; renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were with results from a dynamic heat demand model, previously developed and validated by the authors. 1.compared Main text The results showed that when only weather change is considered, the margin of error could be acceptable for some applications 1. Main text (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation Air pollution and especially urban air pollution is an alarming phenomenon. Exposure to air pollutants can cause scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). Airvalue pollution andcoefficient especially urban aironpollution is an alarming to air pollutants can cause serious health problems, including respiratory problems (asthma, lung irritation, pneumonia, decreased The of slope increased average within the range phenomenon. of 3.8% up to Exposure 8%bronchitis, per decade, that corresponds to the serious health problems, including respiratory problems (asthma, lung irritation, bronchitis, pneumonia, decreased decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
* Corresponding author. Tel.: +40721320403. E-mail address:author. [email protected] * Corresponding Tel.: +40721320403. © 2017 The Authors. Published by Elsevier Ltd. * Corresponding Tel.: +40766255759. E-mail address:author. [email protected] Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and E-mail address:author. [email protected] * Corresponding Tel.: +40766255759. Cooling. E-mail address: [email protected] 1876-6102 © 2018 The Authors. Published by Elsevier Ltd. Keywords: Heat demand; Forecast; Climate change license (https://creativecommons.org/licenses/by-nc-nd/4.0/) This is an open access under the CC BY-NC-ND 1876-6102 © 2018 Thearticle Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the scientific of Technologies and Materials for Renewable Energy, Environment This is an open access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) and Sustainability, TMREES18. Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18. 10.1016/j.egypro.2018.11.321
1554 2
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
resistance to respiratory infections), allergies, cancer and even premature death. Even if significant progress has been made to reduce emissions from industrial sources with a substantial decrease in NO2 concentrations, road traffic has become the first source of emissions in urban areas. Also, authorities must take important decisions to determine people to use public transport or bicycles in order to reduce air pollution and its effects on health and environment hazardous. EURO standards have had a clear benefit in terms of reducing PM emissions from diesel cars, especially from EURO 5 and EURO 6, but not for reducing emissions of NO2. Furthermore, the proportion of diesel cars has increased significantly in many European cities due to the lower cost of diesel fuel, making it obviously the need for nontechnological measures aimed to reduce the use of private cars in cities to meet the pollutant concentration standards. The problem may be even worse in the major cities of Europe due to the higher number of inhabitants and car densities. 2. Measurement sites and techniques This study focuses on the interpretation of 2016-2017 trends for the NO2 concentration from traffic-urban and industrial spaces from two cities in Romania. The two analyzed cities, Galati and Braila, have approximately 430000 inhabitants. The analyzed data are from two traffic monitoring stations and two industrial stations one of each type for each city. Fig.1 provides information on the location of the analyzed areas.
Fig. 1. Location of the monitoring sites considered in this work
3. Results The evaluation of the NO2 concentration level for Braila highlighted the following temporal trends: - in 2016, between January and September, the concentration of NO2 at the traffic station was higher than that recorded at the industrial station; - between October and November, the NO2 concentration at the industrial station recorded a very sharp increase, followed by a decrease towards the end of the year as shown in the figure 2; - in 2017, the NO2 concentration had a similar trend, but the period of sharp increase was recorded for a period of about two times shorter according to Fig. 3;
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
1555 3
- this trend is probably due by the addition at the pollution generated in Braila of the pollution due to intensification of the pollutant transport by the wind from the steel plant located at a distance of 20 km. 250.00
NO2 [µg/m³]
200.00 150.00 100.00 50.00 0.00
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Hours (2016) BR‐4 ‐ industrial
BR‐1 ‐ traffic
Fig. 2. Hourly variation of NO2 concentration measured in Braila at traffic and industrial stations in 2016.
Annual NO2 pollution cycles indicate changes from month to month in the concentration of this pollutant (Fig. 4). The data presented in Fig. 4 are from processing of data provided by the National Air Quality Monitoring Network for Galati and Braila. 400.00 350.00
NO2 [µg/m³]
300.00 250.00 200.00 150.00 100.00 50.00 0.00
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Hours (2017) BR‐4 ‐ industrial
BR‐1 ‐ traffic
Fig. 3. Hourly variation of NO2 concentration measured in Braila at traffic and industrial stations in 2017.
NO2 pollution from traffic in Galati in winter was much more severe than in other seasons, with a maximum value of 93.09 μg / m3, followed by spring (77,33 μg / m3) and autumn (54.94 μg/m3) according to Fig. 5.
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
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120
NO2 [µg/m³]
100 80 60 40 20 1 276 551 826 1101 1376 1651 1926 2201 2476 2751 3026 3301 3576 3851 4126 4401 4676 4951 5226 5501 5776 6051 6326 6601 6876 7151 7426 7701 7976 8251 8526
0
Hours (2016) GL‐1 ‐ traffic
GL‐4 ‐ industrial
Fig. 4. Hourly variation of NO2 concentration measured in Galati at traffic and industrial stations in 2016.
NO2 [µg/m³]
100.00 80.00 60.00 40.00 20.00 1 276 551 826 1101 1376 1651 1926 2201 2476 2751 3026 3301 3576 3851 4126 4401 4676 4951 5226 5501 5776 6051 6326 6601 6876 7151 7426 7701 7976 8251 8526
0.00
Hours (2017) GL‐1 ‐ traffic
GL‐4 ‐ industrial
Fig. 5. Hourly variation of NO2 concentration measured in Galati at traffic and industrial stations in 2017.
During summer months, air pollution with NO2 is lower, but this may be due to higher photochemical air pollution, as there are favorable conditions to O3 production (high temperatures, strong ultraviolet radiation and light winds). Atmospheric pollution with NO2 is higher in winter due to more crowded traffic due to snow and other NO2 sources such as heating systems that increase background concentrations. The weekly cycle highlights daily emissions variations, mainly related to weekly human activities (working week / weekend). The daily cycle shows hour-by-hour changes in pollutant concentrations, this is influenced by traffic intensity and weather conditions that have a major influence on pollutant dispersion and transformation as shown in Fig. 8. From Fig. 6 and 7 it can be noticed that at the traffic station in Galati there are recorded maximum monthly values higher than those of the industrial station. It can be seen that the average monthly value at this type of station is also higher, the concentration being higher in the winter months and lower in the summer months.
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
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Month (2017) Fig. 6. Annual trends of mean, maximum and minimum values of NO2 at traffic station in 2017 for Galati
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Fig. 6 shows the seasonal variation of the NO2 concentration in Galati at the traffic type station in 2017. We can see that the monthly mean concentrations of NO2 are highest in the winter months, probably reflecting the seasonal variation in the lifetime of NO2. 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00
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Month (2017) Fig. 7. Annual trends of mean, maximum and minimum values of NO2 at industrial station in 2017 for Galati
Fig. 6 and 7 show the mean seasonal differences between the NO2 concentrations measured on the same time intervals at the two types of stations. In winter, when the lifetime of NO2 is the longest, the average NO2 concentration is higher than in the summer, due to the shorter summer chemical lifetimes. Spring and autumn show diurnal variations between the winter and summer extremes. In winter, the NO2 concentration increase throughout the day as emissions are higher during the day than during the night. The weekly cycle of NO2 concentration in Galati for traffic and industrial stations is shown in Fig. 8 and 9 for period between January and December 2017. The weekly cycle highlights low concentrations of NO2 on Saturdays and Sundays, which correspond to the weekend pattern and the rest days. We notice significant reductions of NO2 concentration on Saturday and Sunday, with about 40% relative to the weekday mean. The diurnal variation of tropospheric NO2 concentration depends on the diurnal cycle of NO2 emissions and chemical transformations. In urban areas, the NO2 concentrations present maximum daytime values that mainly reflect the intense vehicles use early in the morning and late afternoon.
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Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
Fig. 8. Daily hourly variation of NO2 concentrations at the BR-1 traffic station in 2016
Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
Fig. 9. Daily hourly variation of NO2 concentrations at the BR-1 traffic station in 2017
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Spiru Paraschiv et al. / Energy Procedia 157 (2019) 1553–1560 Author name / Energy Procedia 00 (2018) 000–000
4. Conclusions In 2016 and 2017, at the traffic and industrial measurement type stations in Braila, the hourly average values for NO2 exceeded the European limit value of 40 μg / m3. The observed decrease in NO2 concentration at industrial monitoring stations agrees with the reduction of NO2 emissions from industry due to technology development for pollution reduction. However, the NO2 concentrations at these stations remained either increased and only a reduction of the primarily emitted NO2 due to improved emission control systems alone is not sufficient to reduce the NO2 concentrations significantly. However, the NO2 concentrations at these stations remained higher, and only a reduction of the NO2 emissions due to improved emission control systems alone is not sufficient to reduce the NO2 concentrations. References [1] Spiru Paraschiv, Daniel-Eduard Constantin, Simona-Lizica Paraschiv, Mirela Voiculescu, “OMI and Ground-Based In-Situ Tropospheric Nitrogen Dioxide Observations over Several Important European Cities during 2005–2014”, Int. J. Environ. Res. Public Health 14(11) (2017): 1415, doi:10.3390/ijerph14111415. [2] Anaïs Pasquier, Michel André, “Considering criteria related to spatial variabilities for the assessment of air pollution from traffic”, Transportation Research Procedia 25 (2017): 3354-3369, doi :10.1016/j.trpro.2017.05.210. [3] Sun Chanjuan, Zhang Jialing, Guo Yuchao, Fu Qingyan, Liu Wei, Pan Jun, Huang Yanmin, Zou Zhijun, Huang Chen, “Outdoor air pollution in relation to sick building syndrome (SBS) symptoms among residents in Shanghai, China”, Energy and Buildings 174 (2018): 68-76, doi :10.1016/j.enbuild.2018.06.005. [4] Maryam Shekarrizfard, Ahmadreza Faghih-Imani, Louis-Francois Tétreault, Shamsunnahar Yasmin, Frederic Reynaud, Patrick Morency, Celine Plante, Louis Drouin, Audrey Smargiassi, Naveen Eluru, Marianne Hatzopoulou, “Regional assessment of exposure to traffic-related air pollution: Impacts of individual mobility and transit investment scenarios”, Sustainable Cities and Society 29 (2017): 68-76, doi:10.1016/j.scs.2016.12.002 [5] Paraschiv Lizica-Simona, Paraschiv Spiru Ion V.Ion, “Increasing the energy efficiency of buildings by thermal insulation”, Energy Procedia 128 ( 2017): 393-399, doi:10.1016/j.egypro.2017.09.044. [6] Jean-Marie Cariolet, Morgane Colombert, Marc Vuillet, Youssef Diab, “Assessing the resilience of urban areas to traffic-related air pollution: Application in Greater Paris”, Science of The Total Environment 615 (2018): 588-596, doi:10.1016/j.scitotenv.2017.09.334 [7] Khaled Gasmi, Abdulaziz Aljalal, Watheq Al-Basheer, Mumin Abdulahi, “Analysis of NOx, NO and NO2 ambient levels in Dhahran, Saudi Arabia”, Urban Climate 21 (2017): 232-242, doi :10.1016/j.uclim.2017.07.002 [8] Paraschiv Spiru, Paraschiv Lizica-Simona, “A review on interactions between energy performance of the buildings, outdoor air pollution and the indoor air quality”, Energy Procedia 128 (2017): 179-186, doi:10.1016/j.egypro.2017.09.039. [9] Lizica-Simona. Paraschiv, Spiru Paraschiv, Ion V. Ion, Nicusor Vatachi, “Techno-economic Analysis of the Emissions Reduction Technologies in the Thermal Power Plants in Romania”, J Environ Prot Ecol, 14 (2) (2013): 770. [10] M. Istrate, A. Banica, “Recent dynamics of air pollution from thermal power plants – evidence from Romania, Bulgaria and Greece, Journal of Environmental Protection and Ecology 17, No 3, 831–839, 2016.