Air Quality In Cities Research Articles

Spatio-temporal heterogeneity of air pollution and its key influencing factors in the Yellow River Economic Belt of China from 2014 to 2019

The Yellow River Economic Belt (YREB) plays an important role in China's socio-economic development and ecological security. However, this region has suffered from serious atmospheric pollution in recent years due to intense human activity. Identifying and qualifying the spatio-temporal characteristics of the region's air pollution and its driving forces would help in the formulation of effective mitigation policies. Here, the YREB's spatio-temporal characteristics of air quality were meticulously investigated using air pollution observation, synchronous meteorological, and socio-economic data from 103 cities, for the period of 2014–2019. Furthermore, the factors influencing air pollution were analyzed and qualified. Although air quality improved in the cities of the YREB following the implementation of the Air Pollution Action Plan, the region's quality index (AQI) remained higher than the national average. Annual variations of AQI in the YREB followed a U-shaped pattern, being high in autumn and winter and low in spring and summer; this U shape became shallower following improvements in air quality during autumn and winter. From 2014 to 2019, the annual average AQI values of cities in the eastern, middle, and western YREB dropped from 109.66, 111.70, and 94.65 to 92.00, 103.85, and 73.95, respectively. The air pollution trends of cities revealed obvious spatial agglomeration, and those cities with poor air quality were primarily the western cities of Shandong province, most cities in Henan province, and the eastern cities of Shanxi province. Due to the improvement of air quality in eastern cities, the pollution center of gravity moved gradually from Changzhi (113°3411ʺE, 36°040ʺN) to Linfen (110°5222″E, 36°2344″N). The results of the spatial Durbin model (SDM) indicated that air pollution had an apparent spillover effect in the YREB at the watershed scale, and that government technical expenditure, gross domestic product (GDP) per capita, population density, annual wind speed, and relative humidity all had significant negative overall effects on the AQI values of cities. The green cover rate, ratio of secondary industry, and temperature, meanwhile, all had significant positive total effects. Due to differences the natural conditions and stages of socio-economic development between the eastern, middle, and western cities of the YREB, the impact directions and functional strengths of their key factors differed greatly.

User Perception of the Existence of Arena Youth Park as a Green Open Space in Jambi City

Green Open Space (GOS) is one of the conditions for the formation of a good and healthy city that is beneficial for humans and the environment around the city. In Jambi City Arena Youth Park is one of the GOS and a place for people to do activities such as sports, picnics with family, playgrounds and other activities in Jambi City. This paper aims to determine the user’s perception of Arena Youth Park as a green open space. The method used in this research is quantitative qualitative. The results showed that the typology of green open space in Arena Youth Park was optimal, most of them had met the standards in the Minister of Public Works Regulation No.05/PRT/M/2008. Users of Arena Youth Park tend to engage in recreational activities with a proportion of 49.1%. The variable that has a significant effect on the existence of Arena Youth Park as GOS is Arena Youth Park which affects air quality in cities. As many as 73% of Arena Youth Park users agree that Arena Youth Park is a green open space in Jambi City. With three aspects, namely ecological (72%), socio-cultural (73%) and economic (75%).

Air quality assessment in three East African cities using calibrated low-cost sensors with a focus on road-based hotspots

Poor air quality is a development challenge. Urbanization and industrial development along with increased populations have brought clear socio-economic benefits to Low-and Middle-Income Countries (LMICs) but can also bring disadvantages such as decreasing air quality. A lack of reliable air quality data in East African cities makes it difficult to understand air pollution exposure and to predict future air quality trends. This work documents urban air quality and air pollution exposure in the capital cities of Kampala (Uganda), Addis Ababa (Ethiopia) and Nairobi (Kenya). We build a situational awareness of air pollution through repeated static and dynamic mobile monitoring in a range of urban locations, including urban background, roadside (pavement and building), rural background, and bus station sites, alongside vehicle-based measurements including buses and motorcycle taxis. Data suggest that the measured particulate matter mass concentrations (PM2.5, PM10) in all studied cities was at high concentrations, and often hazardous to human health, as defined by WHO air quality guidelines. Overall, the poorest air quality was observed in Kampala, where mean daily PM2.5 and PM10 concentrations were significantly above the WHO limits at urban background locations by 122% and 69% and at roadside locations by 193% and 215%, respectively. Traffic is clearly a major contributor to East African urban air pollution; monitoring in Kampala and Addis Ababa, on motorcycle taxis, in buses and at bus stations indicated that drivers and commuters were exposed to poor air quality throughout their commute. Road-related air pollution can also impact indoor locations near roads. Using one exemplar building located within Nairobi’s Central Business District, it is shown that measured outdoor PM concentrations significantly correlate with the indoor air quality (r = 0.84). This link between roadside emissions and indoor air pollution within buildings located close to the road should be explored more fully. This study, through a series of case studies, provides clear evidence that roads and traffic need to be a focus for mitigation strategies to reduce air pollution exposure in East African cities.

COLLABORATIVE AIR QUALITY MAPPING OF DIFFERENT METROPOLITAN CITIES OF INDIA

Abstract. Environmental pollution has become extremely serious as a result of today's technological advancements all over the world. One of the most important environmental and public health risks is air pollution. The exponential growth of population, vehicular density on highways, urbanization, and other factors are rising air pollution in cities, necessitating techniques for monitoring and forecasting air quality or determining its health consequences. Various experiments are being conducted on city air quality and its distribution through the built climate. The amount of emissions in the air varies according to the time of day as depicted it is merely high in morning time between 9 to 10 am and between 5 to 6 pm in all cities. These collected data are also characterized as peak hour, average hour, and off-peak hour. It also varies geographically and during special occasions. Since computing and showcasing of air pollution levels require terrain data, air quality data from the open sources i.e. CPCB (central pollution control board, India), and air pollution prediction models. Acculumating the data of the air pollution parameter from the open sources of cities based on typically very crowded, averagely crowded, and thinly crowded areas across the city and then mapping it on ArcGIS. The data monitoring has been done for the whole year merely main emphasizes has been done on the three seasons autumn, winter, and summer (January, May, and August). Also, in winter the value of having pollutants is high due to winter inversion and in the morning also the value is higher, and in monsoon, due to precipitation, it decreases. The dispersion model help in considering the wind speed and direction, the computed data from each source location reaching out to the monitoring sensing station from the comparatively adding to the value of pollutant. With the help of questionnaires, computed out to the result that people residing or having the workplace near to the busy crossing are more promising to have the health-related issue like chocking, respiratory diseases. Men are merely more affected by this between the age of 37 to 63 years.

Impact of Trans-Boundary Pollution (PM-2.5) on the Air Quality of Dhaka City in Bangladesh

Clean air is a basic need of human beings for its existence. In recent years, air pollution in city areas, especially in Dhaka and Chittagong, has become a significant threat to health and well-being. Dhaka is found to suffer a high level of pollution during the dry season, which is from November to April, especially for Particulate Matter, PM2.5, concentration. From December to February this situation is found to be the worst crossing the WHO guidelines and National Ambient Air Quality Standard. Bangladesh is surrounded by countries with the fastest-growing economy like India and China who use coal-burning technologies for different purposes such as producing power and running mills. They release the lion’s share of the air pollutants in South Asia and these pollutants easily get transported to neighboring countries. This is known as transboundary pollution. This study investigates the contribution of transboundary transportation of PM-2.5 in the air quality of Dhaka city. Ninety-Six hours of air mass back trajectories were computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT-4) model and those trajectories were grouped into 6 clusters. Probability calculation showed that Dhaka city air has a higher probability of getting pollutants from long-range sources when air masses traveled through North, West, and North-West direction covering the North Eastern and North-Western territories of India, Nepal, and its neighboring areas. Concentration Weighted Trajectory (CWT) analysis also supported that those areas could be potential sources of getting unwanted PM-2.5 on our atmosphere.
 Chemical Engineering Research Bulletin 21(2020) 114-120

COVID-19 outbreak and air quality of Lahore, Pakistan: evidence from asymmetric causality analysis.

This paper aims to examine the impact of COVID-19 restrictions on the air quality of Lahore city of Pakistan for the period 26th February, 2020 to 31st August, 2020. The study employs asymmetrical Granger causality tests for analyzing the effects of COVID-19 cases and deaths on particulate matter (PM2.5) emissions in the city. The results show positive shocks in COVID-19 cases and deaths improve the air quality of the city. This implies that the pandemic has lowered down environmental pressure in one of the top most polluted cities of the world. Further, the problem of hazardous air pollution in Lahore city is manmade mainly caused by everyday human activities. When these human activities were restricted owing to a rise in COVID-19 cases and deaths, the air pollution in the city resultantly reduces. Therefore, this study recommends controlling unnecessary production and consumption activities that degrades the environment so that air pollution in the city can be manageable after the COVID-19.

The external costs of port activity for port cities: An environmental efficiency analysis of Spanish ports

Port activity brings economic benefits to port cities but also generates negative environmental externalities. These negative externalities derived from pollutants represent a social cost for port cities and coastal areas close to ports, and include costs derived from damages to urban buildings, damage to vegetation and damage to the health of the local population. This raises the question of whether ports may have scope to reduce external costs and thereby improve air quality in port cities and/or increase their existing level of service. To address this, we estimate the environmental efficiency of 37 Spanish ports observed in 2016 for which data on inputs, outputs and local external environmental costs are available. Using Data Envelopment Analysis, we estimate a hybrid model with non-separable good and bad outputs. Undesirable output is measured for the first time by local external costs of air pollution instead of tons of pollutants released, which better reflects the differential damages caused by the individual pollutants. Two definitions of undesirable outputs are used: total local external costs and local external costs per capita. In both versions of the model, we find evidence of high levels of environmental inefficiency in Spanish ports, with over half of the ports found to be inefficient. We rank efficient ports using a super-efficiency version of the model with external costs per capita and identify ports which appear to be references for best practice.

Intra-city variability of fine particulate matter during COVID-19 lockdown: A case study from Park City, Utah

Urban air quality is a growing concern due a range of social, economic, and health impacts. Since the SARS-CoV-19 pandemic began in 2020, governments have produced a range of non-medical interventions (NMIs) (e.g. lockdowns, stay-at-home orders, mask mandates) to prevent the spread of COVID-19. A co-benefit of NMI implementation has been the measurable improvement in air quality in cities around the world. Using the lockdown policy of the COVID-19 pandemic as a natural experiment, we traced the changing emissions patterns produced under the pandemic in a mid-sized, high-altitude city to isolate the effects of human behavior on air pollution. We tracked air pollution over time periods reflecting the Pre-Lockdown, Lockdown, and Reopening stages, using high quality, research grade sensors in both commercial and residential areas to better understand how each setting may be uniquely impacted by pollution downturn events. Based on this approach, we found the commercial area of the city showed a greater decrease in air pollution than residential areas during the lockdown period, while both areas experienced a similar rebound post lockdown. The easing period following the lockdown did not lead to an immediate rebound in human activity and the air pollution increase associated with reopening, took place nearly two months after the lockdown period ended. We hypothesize that differences in heating needs, travel demands, and commercial activity, are responsible for the corresponding observed changes in the spatial distribution of pollutants over the study period. This research has implications for climate policy, low-carbon energy transitions, and may even impact local policy due to changing patterns in human exposure that could lead to important public health outcomes, if left unaddressed.

Has central environmental protection inspection improved air quality? Evidence from 291 Chinese cities

In recent years, central environmental protection inspection (CEPI) has been a major policy innovation in the field of Chinese environmental governance. Based on panel data on the daily air quality of Chinese cities, this paper mainly uses a difference-in-differences (DID) approach to conduct an empirical analysis of the relationship between CEPI and the air quality governance performance of Chinese local governments. There are large differences in the impact of CEPI on different air quality indicators. Controlling for a series of variables, we found that CEPI significantly reduced the air quality index (AQI) and concentrations of pollutants including PM2.5, PM10, SO2 and NO2 and that it significantly increased the concentration of O3; however, it had no significant effect on the concentration of CO. Furthermore, we complemented the quantitative analyses with qualitative evidence gathered from an in-depth interview. Based on the qualitative evidence collected, CEPI indeed plays a role in improving the environmental protection performance of regular environmental governance. Notably, CEPI achieved better and sustainable results in improving air quality through the underlying mechanism of promoting regular governance by campaign-oriented governance in the internal hierarchical system. This article not only provides a marginal empirical contribution by providing new quantitative evidence but also helps reveal the underlying mechanism of promoting regular governance.

The importance of green infrastructure for improving the air quality of Ho Chi Minh city

Ho Chi Minh City is becoming one of the cities which has the highest level of air pollution in Vietnam. The Urban Air Quality Index (AQI) sometimes hits an alarming threshold that shows how contaminated the air is. Air pollution has been set as a major concern for the people of Ho Chi Minh City for more than 20 years after the promulgation of the city developing resolution by the government, by which managing urban is still a challengeable burdensome. Investigating 100 city dwellers upon the issue came uploads of comments of urban citizens towards concerning about alarming polluted air, lacking green spaces, seeking for improvable environmental policies and developing social infrastructures in medication, transport, eco-system, etc. There are some typical solutions like planting more trees, using fewer polluting means of transport, prioritizing the use of clean fuels, using the public transport system, and raising public awareness. Furthermore, generally, citizens can improve their living standards, also enhance their awareness to stop behaving badly to the environment due to ameliorate community consciousness and perform the main role in investing in friendly environmental goods. The research is completed by combining, analysing journal documents and uses methods of an interview as well as a survey to come up with the most effective solutions. To manage the urban environment well, limit pollution, and improve the environment, we need to have long-term strategies. In order to have a good environmental protection strategy, it requires the participation of urban residents. This strategy should be linked to the visions and resolutions in developing industrial planning, transportation, etc. The research initiates multiple solutions for improving the quality of the air in urban places, social medication, and a better environment in the future.

Comparative study on air quality status in Golden Quadrilateral cities before and during the COVID-19 lock down period.

The COVID-19 pandemics have affected every aspect of the human race and the world economy. The disease has been contaminated in almost every part of India. A threat for poor standards induced premature mortality from cardiovascular disease and respiratory diseases. Amongst the huge-reaching implications of the continuing COVID-19 outbreak, a significant enhancement in air quality was detected all around the globe after lockdowns enforced in several cities in India. The lockdown influenced the environment’s pollution level and improved air quality quickly due to very few human activities. The present work scientifically analyses the air pollutants (PM2.5, PM10, NO2, and SO2) with meteorological parameters in the golden quadrilateral cities. The purpose of this paper is to review the analysis of air quality of golden quadrilateral cities (Delhi, Kolkata, Chennai, and Mumbai). Data of air quality parameters are collectively taken from different locations from different regions of Delhi, Kolkata, Chennai, and Mumbai before lockdown and during the lockdown and compared the data of both periods. Comparison pre-lockdown and 2019 with respect to lockdown and 2020 respectively show a huge reduction in amounts of pollutants. Our objective is to find the implication of different lockdown measures on air quality levels in Delhi, Kolkata, Chennai, and Mumbai particularly this investigation is focused on PM2.5, PM10, NO2, SO2 which is directly transmitted by human action and formed through a chemical reaction in the atmosphere as well as quantify the short-range and long-range health impact.

New Chemoresistive Gas Sensor Arrays for Outdoor Air Quality Monitoring: A Combined R&D and Outreach Activities

New Chemoresistive Gas Sensor Arrays for Outdoor Air Quality Monitoring: A Combined R&D and Outreach Activities

SOCAIRE: Forecasting and monitoring urban air quality in Madrid

Air quality has become a central issue in public health and urban planning management, due to the proven adverse effects of airborne pollutants. Considering temporary mobility restriction measures used to face low air quality episodes, the capability of foreseeing pollutant concentrations is crucial. We thus present SOCAIRE (Spanish acronim for “operational forecast system for air quality”), an operational tool based on a Bayesian and spatiotemporal ensemble of neural and statistical nested models. SOCAIRE integrates endogenous and exogenous information in order to predict and monitor future distributions of the concentration for the main pollutants. It focuses on modeling available components which affect air quality: past concentrations of pollutants, human activity, and numerical pollution and weather predictions. This tool is currently in operation in Madrid, producing daily air quality predictions for the next 48 h and anticipating the probability of the activation of the measures included in the city's official air quality NO2 protocols through probabilistic inferences about compound events.

A proposed population-health based metric for evaluating representativeness of air quality monitoring in cities: Using Hong Kong as a demonstration.

City air quality monitoring (AQM) network are typically sparsely distributed due to high operation costs. It is of the question of how well it can reflect public health risks to air pollution given the diversity and heterogeneity in pollution, and spatial variations in population density. Combing high-resolution air quality model, spatial population distribution and health risk factors, we proposed a population-health based metric for AQM representativeness. This metric was demonstrated in Hong Kong using hourly modelling data of PM10, PM2.5, NO2 and O3 in 2019 with grid cells of 45m * 48m. Individual and total hospital admission risks (%AR) of these pollutants were calculated for each cell, and compared with those calculated at 16 monitoring sites using the similarity frequency (SF) method. AQM Representativeness was evaluated by SF and a population-health based network representation index (PHNI), which is population-weighted SF over the study-domain. The representativeness varies substantially among sites as well as between population- and area-based evaluation methods, reflecting heterogeneity in pollution and population. The current AQM network reflects population health risks well for PM10 (PHNI = 0.87) and PM2.5 (PHNI = 0.82), but is less able to represent risks for NO2 (PHNI = 0.59) and O3 (PHNI = 0.78). Strong seasonal variability in PHNI was found for PM, increasing by >11% during autumn and winter compared to summer due to regional transport. NO2 is better represented in urban than rural, reflecting the heterogeneity of urban traffic pollution. Combined health risk (%ARtotal) is well represented by the current AQM network (PHNI = 1), which is more homogenous due to the dominance and anti-correlation of NO2 and O3 related %AR. The proposed PHNI metric is useful to compare the health risk representativeness of AQM for individual and multiple pollutants and can be used to compare the effectiveness of AQM across cities.

Factors influencing improvements in air quality in Guanzhong cities of China, and variations therein for 2014–2020

It is interesting and important to know what factors cause improvements in regional air quality. This study analyzed the factors that improved the air quality in cities in the Guanzhong region of China–in terms of meteorology and controlling emissions–following the implementation of the “Action Plan for Air Pollution Prevention and Control” in 2013. The average air quality index (AQI) values, PM2.5, PM10, SO2, CO, and NO2 in these cities in 2020 decreased by 45.1%, 43.8%, 82.9%, 57.3%, and 31.6%, respectively, compared to the values in 2014, while the O3 concentration increased by 16.7%. During the COVID-19 pandemic of February to May 2020, lockdown measures in cities in Guanzhong resulted in reductions of approximately 18.4%, 24.2%, and 17.9% in the AQI, PM2.5, and PM10 concentrations compared to the same period in 2019. Principal component analysis showed that the yearly reduction in AQI in cities in Guanzhong was attributed mainly to reductions in industrial emissions, followed by reductions in emissions from homes and motor vehicle exhausts. We propose the strengthening of measures to control particulate matter, O3 and greenhouse gas to see the improvement of air quality among this region in the future.

Environmental and health consequences of shore power for vessels calling at major ports in India

To reduce local air pollution, many ports in developed countries require berthed ships to use shore-based electricity instead of burning diesel to meet their electricity requirement for loads such as lights, cargo-handling equipment, and air conditioning. The benefits of this strategy in developing countries remain understudied. Based on government data for all major ports in India, we find that switching from high-sulfur fuel to shore power reduces hoteling emissions of particulate matter (PM2.5) by 88%; SO2 by 39%; NO x by 85%; but increases CO2 emissions by 12%. Switching from low-sulfur fuel reduces hoteling emissions of PM2.5 by 46% and NO x by 84% but increases SO2 emissions by 240% and CO2 emissions by 17%. The lifetime cost savings from the switch to electricity are $73 M for high-sulfur fuel and $370 M for low-sulfur fuel. We estimate that switching from high-sulfur fuel to shore power might avoid at most a couple of dozen premature deaths each year, whereas switching from low-sulfur fuel could lead to a slight increase in premature mortality. Therefore, policymakers must first clean up power generation for shore power to be a viable strategy to improve air quality in Indian port cities.

Air quality in Canadian port cities after regulation of low-sulphur marine fuel in the North American Emissions Control Area

Large marine vessels have historically used high-sulphur (S) residual fuel oil (RFO), with substantial airborne releases of sulphur dioxide (SO₂) and fine particulate matter (PM2.5) enriched in vanadium (V), nickel (Ni) and other air pollutants. To address marine shipping air pollution, Canada and the United States have jointly implemented a North American Emissions Control Area (NA ECA) within which ships are regulated to use lower-sulphur marine fuel or equivalent SO2 scrubbers (i.e., 3.5% maximum fuel S reduced to 1% S in 2012 and 0.1% S in 2015). To investigate the effects of these regulations on local air quality, we examined changes in air pollutant (SO₂, PM2.5, NO₂, O₃), and related PM2.5 components (V, Ni, sulphate) concentrations over 2010–2016 at the Canadian port cities of Halifax, Vancouver, Victoria, Montreal, and Quebec City. SO2 concentrations showed large statistically significant decreases at all sites (−28% to −83% mean hourly change), with the largest improvements in the coastal cities when the 0.1% fuel S regulation took effect. Statistically significant PM2.5 but smaller fractional reductions were also observed (−7% to −37% mean hourly change), reflecting the importance of non-marine PM sources. RFO marker species V and Ni in PM2.5 dramatically declined following regulation implementation, consistent with decreased RFO use likely indicating the switch to low-S distillate fuel oil rather than exhaust scrubbers for initial compliance. Significant changes in other pollutants with non-marine sources (NO2, O3) were not contemporaneous with the regulatory timeline. The large SO2 improvements in the port cities have reduced 1-h concentrations to <30 ppb, comparable to Canadian urban locations with few local SO2 sources and likely reducing health risks to susceptible populations such as asthmatics and the elderly. Our findings indicate that the implementation of the NA ECA improved air quality at Canadian port cities immediately following the requirement for lower-S fuel. These air quality improvements suggest that large-scale international benefits can result from implementation of the 2020 global low-S marine fuel regulations.

Does the New Urbanization Influence Air Quality in China?

Previous studies have empirically investigated the influence of China’s urbanization on atmosphere pollution, the findings in the literature are however controversial and inconclusive across regions, data, and methodologies. This study uses the city-level panel data, 113 key cities of environment protection from the Ministry of Ecology and Environment, covering most of the provinces in China for the period 2013–2017 to investigate the different impacts of the new urbanization pilot policy on air quality and related air pollutants including six major pollutant sources, which are PM2.5, PM10, SO2, CO, NO2, and O3. The study finds that, first, based on the difference-in-difference (DID) method, the new urbanization on average tends to improve the air quality in the pilot cities. Second, based on the quantile DID method, the new urbanization tends to improve the air quality in the lower air quality quantiles (0.1–0.6); however, it has no significant impact in the higher air quality quantiles (0.7–0.9). Third, the impacts of the new urbanization on the air quality vary among different energy-related air pollutants. The new urbanization pilot policy tends to restrain SO2, PM10, and PM2.5, increase CO and O3 and has no impact on NO2. The results indicate that China should pay more attention to promote green consumption and new energy applications and increase urban construction efficiency to further reducing air pollutions in the new urbanization process.

Forecasting the air quality in 18 cities of Henan Province by the compound accumulative grey model

At present, the air quality of most cities in Henan Province is seriously polluted. This will do great harm to people's health and the sustainable development of society. In order to solve this situation and improve the air quality of Henan Province, it is necessary to make effective forecast for the future air quality. After comprehensive consideration of various prediction models, combined with the characteristics of air quality, this paper selects the grey model as the research tool. In order to improve the prediction accuracy of the model, a compound accumulative grey model is proposed in this paper. It has been proved that the accuracy of this model is higher than that of other models. The study found that the concentration of SO2 and NO2 in 18 cities in Henan province will continue to decline, reaching the first-level standard. PM2.5 and PM10 concentrations in all cities still exceeded the standard, with some cities exceeding the standard seriously. In the future, the focus of air control in Henan Province should be on PM2.5 and PM10. The forecast results can provide reference for related departments.

Air Pollution Increases the Incidence of Upper Respiratory Tract Symptoms among Polish Children.

A substantial proportion of airway disease’s global burden is attributable to exposure to air pollution. This study aimed to investigate the association between air pollution, assessed as concentrations of particulate matter PM2.5 and PM10 on the upper respiratory tract symptoms (URTS) in children. A nation-wide, questionnaire-based study was conducted in Poland in winter 2018/2019 in a population of 1475 children, comparing URTS throughout the study period with publicly available data on airborne particulate matter. A general regression model was used to evaluate the lag effects between daily changes in PM10 and PM2.5 and the number of children reporting URTS and their severity. PM10 and PM2.5 in the single-pollutant models had significant effects on the number of children reporting URTS. The prevalence of URTS: “runny nose”, “sneezing” and “cough” was positively associated with 12-week mean PM2.5 and PM10 concentrations. In the locations with the highest average concentration of PM, the symptoms of runny nose, cough and sneezing were increased by 10%, 9% and 11%, respectively, compared to the cities with the lowest PM concentrations. This study showed that moderate-term exposure (12 week observation period) to air pollution was associated with an increased risk of URTS among children aged 3–12 years in Poland. These findings may influence public debate and future policy at the national and international levels to improve air quality in cities and improve children’s health.