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Impact of weather conditions on winter and summer air quality

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The impact of major meteorological elements on the concentration of sulfur dioxide, nitrogen dioxide, particulate matter, and ozone in the extreme conditions of winter and summertime was determined. It was observed that weather conditions significantly contributed to elevated concentrations of the all analyzed pollutants.The impact of thewintertimeweatherwasmost pronounced in southern Poland,whereas in the summer - also in the central and NE parts of Poland. The adverse conditions of anticyclone weather observed in January 2006 had a stronger effect on the concentrations of gaseous pollutants, whereas in July - on tropospheric ozone and particulate matter. Air quality primarily depended on air temperature and wind speed. Air temperature most often explained the variability of summertime ozone and particulate matter immission, aswell aswintertime sulfur dioxide.However, the role of wind speed as a dispersing factor most affected nitrogen dioxide immissions in both seasons, and particulate matter during the winter.
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A b s t r a c t. The impact of major meteorological elements on
the concentration of sulfur dioxide, nitrogen dioxide, particulate
matter, and ozone in the extreme conditions of winter and summer-
time was determined.It was observed that weather conditions sig-
nificantly contributed to elevated concentrations of the all analyzed
pollutants. The impactof the wintertime weather was most pronoun-
ced in southern Poland, whereas in the summer – also in the central and
NE parts of Poland. The adverse conditions of anticyclone weather
observed in January 2006 had a stronger effect on the concentra-
tions of gaseous pollutants, whereas in July – on tropospheric ozo-
ne and particulate matter. Air quality primarily depended on air
temperature and wind speed. Air temperature most often explained
the variability of summertime ozone and particulate matter immis-
sion, as well as wintertime sulfur dioxide. However, the role of wind
speed as a dispersing factor most affected nitrogen dioxide im-
missions in both seasons, and particulate matter during the winter.
K e y w o r d s: season weather conditions, gaseous pollutants,
ozone,particulatematter,airquality
INTRODUCTION
Air quality is determined not only by the amount of
emissions, but also by current and preceding meteorological
conditions. The effect of weather on dispersion of gases and
particulate matter (PM10), and on their deposition within the
ground layer of air, has been demonstrated in a number of
studies (Czarnecka and Nidzgorska-Lencewicz, 2008; Elminir,
2005; Jacob and Winner, 2009; Malek et al., 2006). Episodes
of sudden intense air pollution, referred to as smog, which
occur within large urban agglomerations and industrial areas,
pose a serious threat to human health. The negative impact
of high pollutant concentration on environment has been
thoroughly studied and widely documented (Amann et al.,
2008; Filleul et al., 2006; Fischer et al., 2004; Stedman,
2004; WHO, 2006). In August 2003, a very high level oftropo-
spheric ozone (O3) was recorded across Europe(Solberg et al.,
2008), which, in conjunction with other pollutants and a heat
wave, resulted in a considerable increase in mortality.
Filleul et al. (2006) demonstrated that between the 3rd and
the 17th of August 2003, the risk of death due to high 8 h
concentrations of O3in connection with high temperatures
increasedfrom10.6%in LeHavre to174.7%in Paris.
The so-called black smog occurring in winter and the
photochemical smog observed in spring and summer are both
correlated with anticyclone weather, vertical thermal structu-
re of the atmospheric boundary layer, and the type of circula-
tion (God³owska, 2004; Malek et al., 2006; NiedŸwiedŸ and
Ustrnul, 1989; Walczewski, 1997). Topography that ham-
pers natural air circulation of a city, can contribute to the
rise, buildup, and duration of smog episodes. Tall, tightly-
packed buildings present an additional barrier to the disper-
sion of pollutants in metropolitan areas (Xie et al., 2005).
Because air pollution is affecting an increasing number of
people worldwide, especially in urban areas, continuous air
quality monitoring is a necessity. Forecasting is also impor-
tant since it enables early warning of high pollution levels
and allows more time to prepare and reduce exposure (Krupa
et al., 2003; Ma et al., 2004; Schicker and Seibert, 2009;
Walczewski, 1997). During the winter and summer of 2006,
extreme weather conditions in Poland led to an increase in
concentrationsofsomepollutantsbeyondthelimitlevel.
The aim of this study is to evaluate the effect of major
meteorological parameters on elevated and limit-exceeding
concentrationsofpollutantsaffectingairquality.
Int.Agrophys.,2011,25,7-12
Impactofweatherconditionsonwinterandsummerairquality
M.CzarneckaandJ.Nidzgorska-Lencewicz
DepartmentofMeteorologyandClimatology,WestPomeranianUniversityofTechnology,
Papie¿aPaw³aVI3,71-434Szczecin,Poland
ReceivedJune22,2010;acceptedSeptember2, 2010
©2011InstituteofAgrophysics,PolishAcademyofSciences
*Corresponding author’s e-mail:malgorzata.czarnecka@zut.edu.pl
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www.international-agrophysics.org
MATERIALSANDMETHODS
This study was based on data recorded by the automatic
air quality monitoring system of National Environment
Monitoring. The data comprised hourly concentrations of
sulfur dioxide (SO2), nitrogen dioxide (NO2), PM10, and
O3, collected during winter (December 2005 to February
2006) and summer (June to August 2006) from immission
stations operating in 12 places of Poland (Fig. 1). The primary
selection criterion for a station was the completeness of
measuring immissions and meteorological data. All of the
stations are located in urban area. The meteorological data
collected by automatic stations located near the immission sta-
tions included total radiation, air temperature, atmospheric
pressure, relative air humidity, and wind velocity. Hourly
and daily concentrations of the analyzed air pollutants were
evaluatedaccordingtothestandards.
The effects of these meteorological parameters on the
concentrations of the analyzed pollutants were estimated
using correlation analysis, as well as, single and multiple re-
gression, including stepwise analysis. The analysis was per-
formedatsignificancelevelsof a=0.05and a=0.01.
RESULTS
In 2006, the mean annual temperature in Poland was
0.8ºC higher than the long-term average, and the annual
precipitation was approx. 96% of the average for the period
between 1971 and 2000 (Bulletin, 2006). However, both
thermal patterns and precipitation demonstrated very strong
fluctuations between the seasons and between consecutive
months. The greatest difference in weather was between
winter and summer, and, in particular, between January and
July. In terms of temperature and precipitation, January and
July clearly deviated from their respective monthly means of
previous years (Fig. 2). Most days in January the weather
was characterized by an extensive Russian high pressure
area which brought mass amounts of frosty, dry air to Poland.
The mean temperature for the month typically ranged from
-4 to -8.5ºC and was more than 5ºC lower than the long-term
average in the majority of cities. July was extremely hot and
dry. The mean temperature for July in whole Poland ranged
from 21 to 25ºC, which exceeded the average by 3 to 6ºC.
Precipitation in July 2006 was merely 25% of the long term
average. In both months, under anticyclone weather condi-
tions, the mean monthly wind speed in the urban areas did
not exceed 1.5 m s-1, which considerably reduced natural
dispersionofpollutedair.
Due to severe frosts in January 2006, an increase in the
use of heaters occurred in urban and residential areas. Poor
air circulation in these areas resulted in considerably higher
immission of the main pollutants, especially in southern
Poland. The mean monthly concentrations of SO2ranged
between 15 and 50 µg m-3, while concentrations of PM10
usually ranged between 50 and 150 µg m-3. The highest
mean concentrations of SO2and NO2was recorded in the
D¹browa Górnicza, while PM10 was highest near Kraków.
In January 2006, mean monthly concentrations of SO2were
twice as high, and PM10 were three times higher then the
averages for 1993 to 2002 (Czarnecka and Kalbarczyk, 2004),
and still much higher compared with adjacent years (Fig. 3).
Air quality across the country fell well below standards,
especially regarding the 24 h concentrations of PM10. The
highest daily PM10 concentrations were recorded in the last
ten days of January. In northern Poland (Szczecin, Gdañsk),
the concentrations of PM10 were six times that of the ac-
ceptable 24 h limit, and in the south (Kraków), more than ten
times (Fig. 4). In most of the analyzed cities, alarm levels of
concentrations were exceeded, meaning the mean hourly
8 M.CZARNECKAandJ.NIDZGORSKA-LENCEWICZ
Fig. 1. Location of urban immission stations considered in the
study.
0
40
80
120
160
2005 2006 2007 2008 2005 2006 2007 2008
-10
0
10
20
30
Kraków
JanuaryJuly
0
40
80
120
160
2005 2006 2007 2008 2005 2006 2007 2008
-10
0
10
20
30
Szczecin
P (mm)
T (C)
o
T (C)
o
P (mm)
Fig. 2. Air temperature (T) and total precipitation (P) in January
andJulyin Szczecin andKrakówduring2005-2008.
values were exceeded by 2 to 13 days (Fig. 5). These anoma-
lies were the most frequent in Kraków, where the hourly
PM10 concentrations on January 17, 25, and 27 of reached
505, 592, and 507 ìg m-3, respectively. These concentra-
tions exceeded the maximum smog episode concentrations
for January 2006 by 100 to nearly 200 ìg m-3 (Mira-Salama
etal.,2008).
In July 2006, the level of PM10 dust was considerably
elevated compared to previous years. O3levels were also
high, but they did not differ much from O3levels in 2005
(Fig. 6). Nevertheless, immission levels of all pollutants
oscillated below the allowable threshold. Only in Jelenia
Góra, D¹browa Górnicza, and Radom, did the hourly O3con-
centrations exceed the level of 180 ìg m-3, on 20-21 July,
which, according to the alarm rule, requires that the public
beinformedaboutahighriskofasmogevent.
The impact of weather conditions on the variability of
pollutant levels in 2006 was demonstrated using the coeffi-
cients of determination, in most cases statistically signifi-
cant at a= 0.01 (Table 1). Over the entire country, and in
both winter and summer, the coefficients ranged between 10
and 30%, reaching, however, much higher values in most
cities. The impact of the 2005/2006 winter weather was
slightly stronger in relation to the immission of PM10 and
SO2, and weaker in relation to NO2(Table 1). In most of the
cities, the role of inclement weather in the pattern of changes
in pollutant immission was more apparent in January than in
the overall winter of 2005/2006, particularly in relation to
NO2. The impact of the winter weather conditions was most
apparent in southern Poland. The highest coefficients of de-
termination for SO2and PM10, approx. 83 and 70%, respec-
tively, for January were recorded in Radom. On the other
hand, the impact of weather on NO2immission changes was
most evident within the local topography of Jelenia Góra,
whereJanuaryR2reachednearly71%.
IMPACTOFWEATHERCONDITIONSONWINTERANDSUMMERAIRQUALITY 9
0
50
100
150
200
2005 2006 2007 2008
0
10
20
30
40
50
2005 2006 2007 2008
SO (µg m )
2
-3
PM10 (µg m )
-3
Szczecin
Szczecin
0
10
20
30
40
50
2005 2006 2007 2008
Kraków
0
50
100
150
200
2005 2006 2007 2008
winter January
Kraków
Fig. 3. Mean concentrations of particulate matter (PM10) and sulfur dioxide (SO2) during wintertime of 2005-2008 in Szczecin and
Kraków.
0
150
300
450
600
1 4 7 10 13 16 19 22 25 28 31
PM10 (µg·m-3)
GdaDsk
Szczec in Krak ów
st anda rd
(days)
Gdañsk
Fig. 4. Mean 24 h concentrations of particulate matter (PM10) in
January 2006in selectedcitiesof Poland.
Gdansk
Dabrowa
Fig. 5. Number of days in January 2006 when alarm (hourly) levels
ofPM10wereexceeded.
The meteorological conditions of summer 2006 best
described the variability of O3and PM10 concentrations,
and were much less responsible for the levels of NO2. In many
cities, however, the adverse effect of weather on NO2
immission was most pronounced in July. Extremely high
July coefficients of determination, as compared with the
entire summer, were observed in Olsztyn, Radom, and
Rzeszów. The most apparent effect of weather on tropo-
spheric O3concentrations (R2~ 70%) was demonstrated in
£ódŸ and Jelenia Góra. However, in D¹browa Górnicza the
relationship between the weather and PM10, as well as NO2,
was the strongest. In general, the variability of PM10 con-
centrations depended on bad weather conditions stronger in
the summer of 2006 than in the winter; however, the para-
meter varied between regions and, in some of the cities, the
relationshipswerenotsignificant.
10 M.CZARNECKAandJ.NIDZGORSKA-LENCEWICZ
0
20
40
60
80
2005 2006 2007 2008
O (µg m )
3
-3
Szczecin
0
20
40
60
80
2005 2006 2007 2008
Kraków
0
20
40
60
2005 2006 2007 2008
PM10 (µg m )
-3
summer July
0
20
40
60
2005 2006 2007 2008
Fig.6. Meanconcentrationsofparticulatematter(PM10)andozone(O3)duringsummertimeof2005-2008in Szczecin andKraków.
City
2005/2006 2006
SO2NO2PM10 O3NO2PM10
winter January winter January winter January summer July summer July summer July
Szczecin 40.5 44.7 38.8 54.2 52.1 52.5 56.3 42.9 20.9 n.s. 53.7 11.6
Gdañsk 51.2 53.4 33.6 48.9 33.2 36.8 28.5 22.9 13.3 29.2 34.2 56.2
Olsztyn 26.4 40.0 22.5 39.3 35.2 15.3 25.6 35.3 9.8 56.5 46.1 55.5
Warszawa 26.9 21.9 38.4 53.5 45.6 48.2 58.8 42.2 27.1 28.4 49.9 71.3
£ódŸ 29.4 32.7 26.8 49.6 40.6 51.1 72.5 68.8 14.6 31.4 59.3 43.8
Poznañ 10.9 25.8 5.0 38.8 5.3 36.5 63.7 54.2 18.7 20.2 42.7 37.3
Jelenia
Góra 63.8 67.4 52.4 70.7 45.2 49.0 54.7 70.8 23.4 34.6 48.3 41.4
Opole 33.6 17.1 38.4 46.2 29.7 25.3 * * 18.2 28.5 50.6 52.0
D¹browa
Górnicza 50.8 43.8 41.6 57.2 45.7 49.6 50.4 42.8 50.3 61.4 73.0 74.8
Kraków 41.5 19.7 37.6 41.5 57.0 49.7 * * 9.7 33.7 44.4 n.s.
Radom 68.5 83.4 46.7 68.8 57.0 69.6 61.0 46.6 4.7 33.1 64.4 74.5
Rzeszów 45.1 75.9 25.3 53.8 54.4 64.0 * * 15.5 40.9 22.0 n.s.
Poland 23.7 16.0 24.5 22.7 33.7 28.7 * 32.0 7.8 12.8 32.0 18.6
*lackofdata,n.s.–nonsignificantrelationshipsat a=0.05.
T a b l e 1. Coefficients of determination (%) for the relationship between SO2, NO2, PM10 (2005/2006) and O3, NO2, PM10 (2006)
concentrations versus nominatedmeteorologicalcomponents
The air quality in Poland during winter and summer
2006 depended mostly on air temperature and wind speed.
The role of these factors in the variability of immission, as
expressed by the coefficient of partial determination,
differed depending on the type of pollution and the season
(Fig. 7). In the winter, SO2immission was primarily deter-
mined by air temperature, whereas NO2was most affected
by wind speed. The most similar coefficients of partial de-
termination for both meteorological components were esti-
mated for PM10 dust; during the entire winter, air tempera-
ture was more important in explaining its concentrations,
and wind speed in January alone. An increase in the
concentrations of O3and NO2in July 2006 was in large part
due to air thermal conditions. Air temperature and wind speed
played an important role in the pattern changes of PM10
particulate matter immission. In July, the impact of both was
nearly the same, while if we look over the entire summer
period, air temperature was the main factor underlying the
immissionincrease.
Adverse weather conditions that significantly influen-
ced the levels and variability of SO2, NO2, and PM10 con-
centrations in selected cities of Poland in 2006 most often
represented two meteorological components at a time, nomi-
nated using the stepwise procedure of regression analysis.
Air temperature and wind speed were most frequently nomi-
nated, similar as in the scope of the entire country; however,
also relative humidity, pressure, and total radiation represen-
ted the variables accounting for the magnitude of immission
(Fig. 8). These elements are commonly named in the literature
as major factors that lead to air quality deterioration, also in
different climatic zones. The role of thermal conditions as
the main factor increasing the emission and, in consequence,
the immission of major wintertime pollutants, in association
with anemometric conditions, was demonstrated by many
authors, including God³owska (2004), Majewski and Prze-
woŸniczuk (2006), Malek et al. (2006), Mira-Salama et al.
(2008), Schicker and Seibert (2009), usually basing on a de-
tailed analysis of occurrence of certain smog episodes or their
models. Air temperature and wind speed are also used for
describing and forecasting high O3levels (Baran et al., 1999;
Palacios et al., 2004).
The effect of temperature on pollution levels depended
ontheseason. In winter,temperatureincreaseresultedina drop
in the immission of all pollutants, whereas in summer, it con-
tributed to an increase. Wind speed always positively in-
fluenced air quality, and even under anticyclonic weather
conditions, regardless of the wind direction, the ventilation
function of wind was apparent. Interestingly, total radiation
frequently (>20% of cases) explained radiation and thermal
conditions which deteriorate air quality. In the summer,
however, such conditions were reflected only by the 24 h
mean air temperature. Temperature was the most important
variable explaining the flux in O3concentrations, which
agreed with the results of Gzella and ZwoŸdziak (2003),
Elminir(2005)andJacobandWinner(2009).
Air temperature most often accounted for the variability
of O3and PM10 immission in summer, and, in July, in 80%
of the cases. In winter, thermal conditions were the main
factor explaining SO2concentration variability. In regres-
sion equations, which described immission of NO2and
PM10, wind speed most frequently explained variability.
Moreover, wind speed most often determined NO2concen-
trations during the summer. An increase in relative air humi-
dity contributed to reduced immissions of all the analyzed
pollutants during the winter. However, humidity most fre-
quently ie in about 40% of the cases, significantly explained
O3concentrationsduringthesummer.
IMPACTOFWEATHERCONDITIONSONWINTERANDSUMMERAIRQUALITY 11
Fig. 7. Coefficients of partial determination (%) of meteorolo-
gical components affecting the variability of pollutant concentra-
tions during the winter and summer 2006 in the scope of the entire
country.
Fig. 8. Frequency of meteorological components (%) accounting
for the concentration variability of the analyzed pollutants in the
consideredcitiesduringthewinterandsummer2006.
CONCLUSIONS
1. The meteorological conditions during winter and
summer 2006, especially in January and July, were the
fundamental cause underlying air quality decline in urban
areas of Poland. During the winter of 2005/2006, the
weather had the strongest impact on air quality in the cities
of southern Poland; in summer 2006, also in the central and
northeasternpartsofthecountryweremostlyaffected.
2. Adverse anticyclonic weather in January 2006 had
a strong impact on the concentrations of gaseous pollutants
ie NO2and SO2, and in July, on tropospheric O3and PM10.
3. The air quality in 2006 was determined mainly by air
temperature and wind velocity. Air temperature most often
accounted for the variability of O3and PM10 particulate
matter immission during the summer, and SO2during the
winter. However, concentrations of NO2in both seasons,
and PM10 in the winter, were determined primarily by
wind speed.
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12 M.CZARNECKAandJ.NIDZGORSKA-LENCEWICZ
... Floods and similar extreme events are consequences of climate change that are expected to occur more frequently and have catastrophic effects in years to come (Yucel, Onen, Yilmaz, & Gochis, 2015). More interestingly, recent studies have highlighted that weather conditions can potentially increase air pollution (another major topic of discourse alongside climate change in recent times) in winter and summer periods (Czarnecka, Nidzgorska-Lencewicz, et al., 2011). It is pertinent to reiterate that increased air pollution results in health conditions such as asthma and similar problems related to the lungs (Mokrani, Lounas, Bennai, Salhi, & Djerbi, 2019;Zadtootaghaj, Mohammadian, Mahbanooei, & Ghasemi, 2019). ...
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Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statistical models that are often too costly, both computationally and budgetary, or are not applied to downstream applications. Therefore, approaches that use Machine Learning algorithms in conjunction with time-series data are being explored as an alternative to overcome these drawbacks. To this end, this study presents a comparative analysis using simplified rainfall estimation models based on conventional Machine Learning algorithms and Deep Learning architectures that are efficient for these downstream applications. Models based on LSTM, Stacked-LSTM, Bidirectional-LSTM Networks, XGBoost, and an ensemble of Gradient Boosting Regressor, Linear Support Vector Regression, and an Extra-trees Regressor were compared in the task of forecasting hourly rainfall volumes using time-series data. Climate data from 2000 to 2020 from five major cities in the United Kingdom were used. The evaluation metrics of Loss, Root Mean Squared Error, Mean Absolute Error, and Root Mean Squared Logarithmic Error were used to evaluate the models’ performance. Results show that a Bidirectional-LSTM Network can be used as a rainfall forecast model with comparable performance to Stacked-LSTM Networks. Among all the models tested, the Stacked-LSTM Network with two hidden layers and the Bidirectional-LSTM Network performed best. This suggests that models based on LSTM-Networks with fewer hidden layers perform better for this approach; denoting its ability to be applied as an approach for budget-wise rainfall forecast applications.
... Researchers have already determined that the AQI value is significantly affected by the season. In addition concentration of air pollution are associated with temperature and wind speed, according to Czarnecka and Nidzgorska-Lencewicz [78]. Therefore, the number of crimes could change seasonally, whereas if the AQI values change, the number of crimes could either increase or decrease depending on the type of crime. ...
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Air pollution has a severe impact on human physical and mental health. When the air quality is poor enough to cause respiratory irritation, people tend to stay home and avoid any outdoor activities. In addition, air pollution may cause mental health problems (depression and anxiety) which were associated with high crime risk. Therefore, in this study, it is hypothesized that increasing air pollution level is associated with higher indoor crime rates, but negatively associated with outdoor crime rates because it restricts people’s daily outdoor activities. Three types of crimes were used for this analysis: robbery (outdoor crime), domestic violence (indoor crime), and fraud (cybercrime). The results revealed that the geographically and temporally weighted regression (GTWR) model performed best with lower AIC values. In general, in the higher population areas with more severe air pollution, local authorities should allocate more resources, extra police officers, or more training programs to help them prevent domestic violence, rather than focusing on robbery.
... Weather conditions significantly affect the dynamics of the atmosphere, gas transformation processes and the transportation of pollutants [72,73]. For this reason, meteorological parameters are usually monitored simultaneously with air quality ones, in order to characterize their relationship. ...
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... One of the reasons for this phenomenon is that coal has been the main source of energy in China for a long time, and coal burning in coal-fired boilers and power plants is especially common in winter for heating and in summer for cooling. The article [3] assesses the influence of meteorological conditions on the variability of the concentration of sulfur dioxide and solid particles during the winter in Poland. The analysis covers calendar winters (December -February) within the period between 2004/2005 and 2009/2010. ...
... The article [3] assesses the influence of meteorological conditions on the variability of the concentration of sulfur dioxide and solid particles in Poland during winters. The analysis covers calendar winters (December-February) within the period between 2004/2005 and 2009/2010. ...
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... Further analysis was conducted separately for those two groups in order to study the performance of the modeled air temperature forecast in relation to local environmental conditions. The stations/measurement points represented the main types of relief of the Polish Western Carpathians: high mountains (8); areas at the foot of high mountains (7,14); mountain tops in the Beskidy Mts. (10, 12, 15, and 17); valley bottoms in the Beskidy Mts. ...
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