Average Concentrations Of SO2 Research Articles

International airport emissions and their impact on local air quality: chemical speciation of ambient aerosols at Madrid–Barajas Airport during the AVIATOR campaign

Abstract. Madrid–Barajas Airport (MAD) is the fourth-busiest airport in Europe. The aerosol chemical composition and the concentrations of other key pollutants were measured at the airport perimeter during October 2021 to assess the impact of airport emissions on local air quality. A high-fidelity ambient instrumentation system was deployed at Madrid–Barajas Airport to measure the following: concentrations of organic aerosols (with their composition), black carbon (eBC), carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NOx), sulfur dioxide (SO2), particulate matter (PM2.5, PM10), total hydrocarbon (THC), and total particle number. The average concentrations of eBC, NOx, SO2, PM2.5, PM10, CO, and THC at the airport for the entire campaign were 1.07 µg m−3, 22.7 µg m−3, 4.10 µg m−3, 9.35 µg m−3, 16.43 µg m−3, 0.23 mg m−3, and 2.30 mg m−3, respectively. The source apportionment analysis of the non-refractory organic aerosol (OA) using positive matrix factorisation (PMF) allowed us to discriminate between different sources of pollution, namely less oxidised oxygenated organic aerosol (LO-OOA), alkane organic aerosol (AlkOA), and more oxidised oxygenated organic aerosol (MO-OOA). The results showed that LO-OOA and MO-OOA account for more than 80 % of the total organic particle mass measured near the runway. Trace gases correlate better with the AlkOA factor than LO-OOA and MO-OOA, indicating that AlkOA is mainly related to primary combustion emissions. Bivariate polar plots were used for pollutant source identification. Significantly higher concentrations of the obtained factors were observed at low wind speeds (<3 m s−1) from the southwest, where two of the runways and all terminals are located. Higher SO2/NOx and CO/eBC ratios were observed when the winds originated from the northeast, where the two northern runways are located. These elevated ratios are attributed to the aircraft activity being the major pollutant source in the northeast area.

Simulating air pollution at the province level: A case of Ba Ria – Vung Tau province, Vietnam

Abstract This study aimed to simulate air pollution in Ba Ria - Vung Tau province (BR-VT), a significant transportation hub in Vietnam and Southeast Asia. The FVM-TAPOM model system was employed to create a spatial distribution map of air pollution concentration including PM2.5, PM10, NO2, SO2, and CO. The model had sufficient capability for simulating air pollutant distribution (R2>0.6). For PM2.5, the average simulated 1-hour PM2.5 concentration is highest during the dry and rainy seasons, reaching 68 μg/m3 and 46 μg/m3, respectively. For PM10, the average 1-hour simulated PM10 dust concentration is highest during the dry and rainy seasons, reaching 90 μg/m3 and 62 μg/m3, respectively. For NO2, the average 1-hour simulated NO2 concentration is highest during the dry and rainy seasons, reaching 56 (μg/m3) and 46 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 200 μg/m3). For SO2, the average 1-hour simulated SO2 concentration is highest during the dry and rainy seasons, reaching 140 μg/m3 and 88 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 350 μg/m3). For CO, the average 1-hour simulated CO concentration is highest during the dry and rainy seasons, reaching 2.950 μg/m3 and 2.280 μg/m3, respectively, which is lower than the permissible threshold of QCVN 05:2023/BTNMT (1-hour average 30.000 μg/m3).

Anthropogenic and biogenic pollutants in a forested environment: SPRUCE-22 campaign overview

The SPRUCE-22 field campaign was conducted during July 2022 on a remote mountainous forested site in Greece to assess interactions of biogenic and anthropogenic pollutants in the Eastern Mediterranean. Particle chemical composition and size distributions along with concentrations of organic and inorganic gases were measured at high temporal resolution, while samples were collected and analyzed off-line. PM1 had a surprisingly high average concentration of 13 μg m−3 consisting primarily of organics (57%), followed by sulfate (30%), ammonium (9%), and black carbon (2%). Nitrates (both inorganic and organic) were less than 1% of the PM1 despite the relatively high NOx emissions in the Balkans. The PM2.5 concentrations at this remote site were similar and even higher than those in major cities across Greece including Athens, indicating the importance of regional transport for summertime pollution in the Eastern Mediterranean. The relatively constant average diurnal profiles of major anthropogenic pollutants are consistent with only minimal effects from local sources. Sulfates are not any more the dominant component of fine PM in Greece due to the reduction of SO2 emissions of coal-burning powerplants. The organic aerosol (OA) was quite oxidized with an average oxygen to carbon ratio (O:C) equal to 0.83. The average concentration of isoprene was 0.6 ppb, of monoterpenes 0.5 ppb, while the biogenic secondary organic aerosol factor (obtained through source apportionment analysis) was estimated to contribute 22% of the OA. Additional biogenic secondary organic aerosol (SOA) may be part of the two oxygenated OA (OOA) factors that were also identified. Radiocarbon analysis indicated that the non-fossil carbon was approximately equal to the sum of the biogenic and the more oxidized oxygenated OA, implying that the less oxidized OOA in this study was mostly associated to anthropogenic fossil fuel combustion. The biogenic SOA was quite aged (O:C equal to 0.63) and was also mostly transported to the site. Nearby new particle formation events occurred during 20 % of the days, with an average SO2 concentration of 0.3 ppb. The oxidative potential of the PM per unit of mass was quite high. The source attribution of the fine PM and the interactions among its anthropogenic and biogenic components are also discussed.

Particulate and gaseous air pollutants exceed WHO guideline values and have the potential to damage human health in Faisalabad, Metropolitan, Pakistan

First-ever measurements of particulate matter (PM2.5, PM10, and TSP) along with gaseous pollutants (CO, NO2, and SO2) were performed from June 2019 to April 2020 in Faisalabad, Metropolitan, Pakistan, to assess their seasonal variations; Summer 2019, Autumn 2019, Winter 2019–2020, and Spring 2020. Pollutant measurements were carried out at 30 locations with a 3-km grid distance from the Sitara Chemical Industry in District Faisalabad to Bhianwala, Sargodha Road, Tehsil Lalian, District Chiniot. ArcGIS 10.8 was used to interpolate pollutant concentrations using the inverse distance weightage method. PM2.5, PM10, and TSP concentrations were highest in summer, and lowest in autumn or winter. CO, NO2, and SO2 concentrations were highest in summer or spring and lowest in winter. Seasonal average NO2 and SO2 concentrations exceeded WHO annual air quality guide values. For all 4 seasons, some sites had better air quality than others. Even in these cleaner sites air quality index (AQI) was unhealthy for sensitive groups and the less good sites showed Very critical AQI (> 500). Dust-bound carbon and sulfur contents were higher in spring (64 mg g−1) and summer (1.17 mg g−1) and lower in autumn (55 mg g−1) and winter (1.08 mg g−1). Venous blood analysis of 20 individuals showed cadmium and lead concentrations higher than WHO permissible limits. Those individuals exposed to direct roadside pollution for longer periods because of their occupation tended to show higher Pb and Cd blood concentrations. It is concluded that air quality along the roadside is extremely poor and potentially damaging to the health of exposed workers.Graphical abstract

Groundwater quality and health risk assessment of nitrate and fluoride in Al Qaseem area, Saudi Arabia

Abstract Groundwater serves as the lifeline in arid regions, where aquifer overuse and climatic factors can substantially degrade its quality, posing significant challenges. The current study examines the drinking water quality in the Al Qaseem area and assesses the potential health risks from nitrate ( NO 3 − {\text{NO}}_{3}^{-} ) and fluoride (F−) exposure to infants, children, and adults. This evaluation employs parameters such as the daily water intake, hazard quotient, and non-carcinogenic hazard index. Groundwater samples from 38 wells and boreholes were analyzed for major cations and anions. The water quality index and multivariate tools were utilized. The average concentrations of SO 4 2 − {\text{SO}}_{4}^{2-} , Cl–, Ca+, Na+, Mg2+, and K+ exceeded acceptable limits. Among the 38 samples, 8 were unsuitable for drinking, with 5 categorized as very poor quality, 10 as poor, 14 as good, and 1 as excellent. Nitrate levels ranged from 1.30 to 108.00 mg/L, with a mean of 36.56 mg/L. Three wells exceeded World Health Organization (WHO) guidelines (50.00 mg/L). Fluoride ranged from 0.10 to 0.98 mg/L, with a mean of 0.71 mg/L and none surpassing WHO recommendations (1.5 mg/L). The HI values for adults, children, and infants were 0.993, 2.606, and 2.78, respectively. About 57.89% of the water samples exceeded the safety level of 1 for adults and 94.73% for both children and infants. Thus, the groundwater in the study area may pose non-carcinogenic health risks to infants, children, and adults when used as drinking water.

Comparative study of air quality index of two metropolitan cities (Lucknow and Kanpur) in Year-2023

In 2023, it was declared that the Bangladesh at the first place and then Pakistan, after which the most polluted country is India at the third place. Polluted air is becoming a very considerate issue all over the world. This study is all about comparing the air quality of two metro cities, Lucknow and Kanpur during (November 2022- October,2023) buy monitoring and assessment of few selective basic AQI air pollutants namely Particulate Matter (PM10) , Sulphur dioxide (SO2), Nitrogen dioxide (NO2) concentrations and also AQI of Lucknow and Kanpur at 5 representative locations categorized as residential, commercial and industrial areas. Residential area in Lucknow (Mahanagar and Aliganj) and in Kanpur (Kidwai Nagar and Shastri Nagar), Commercial areas in Lucknow (Hazarat Ganj and Ansal T.C.) and in Kanpur (Zareeb Chauki and Ramadevi), Industrial area Talkatora in Lucknow and Panki in Kanpur have been taken under consideration. The result found that 24 hours concentration of PM10 were in the range of 76.40 to 261.19 µg/m3 in Lucknow and 74.68 to 400.67 µg/m3 in Kanpur with an average of 174.34 and 160.36 µg/m3, respectively. The average value of PM10 was above as per the guideline of WHO and permissible limit prescribed by NAAQ in both the cities. Similarly, 24 hours average concentration of SO2 was below the prescribed level of NAAQ in Lucknow and Kanpur which was in the range of 5.33 to 12.70 µg/m3 in Lucknow and 2.00 to 9.53 µg/m3 in Kanpur with an average of 8.71 and 7.19 µg/m3, respectively. The 24 hours average concentration of Nitrogen dioxide (NO2) was below prescribed level of NAAQ in Lucknow and Kanpur. In Lucknow it was in the range of 13.83 to 48.01 µg/m3 and in Kanpur 21.45 to 64.02 µg/m3 with an average of 29.45 and 50.14 µg/m3, respectively. The 24 hours AQI was reported in the range of 76 to 211 in Lucknow and 75 to 363 in Kanpur with an average of 150.84 and 142.76 respectively which is greater moderate to severe by NAAQ and WHO guideline throughout the year. Ultimately, this entire study is related to human health because polluted air gives rise to various hazardous diseases such as asthma cancer, premature death cardiovascular diseases, respiratory tract diseases etc.

Insights into civil aviation emissions in China: Analysis of an emission inventory of air pollutants and the ChinaHighAirPollutants (CHAP) dataset

The emissions from the civil aviation sector are a significant source of CO2 and air pollutants, which represent a serious threat to ambient air quality and public health. To gain a deeper understanding of civil aviation airport emissions, it is imperative to develop a precise and comprehensive emission inventory of China's civil aviation airports. However, there are limited studies dedicated to analyzing and verifying the accuracy and completeness of China's civil aviation emission inventory. Here, this study explored pollution characteristics from temporal trends and spatial distribution perspectives based on a previously developed 2019–2020 high-resolution air pollution and CO2 emission inventory of the landing and take-off (LTO) cycle of civil aviation airports in China and the ChinaHighAirPollutants (CHAP) dataset. Besides, this study established an empirical model to evaluate the relationship between the air pollutant emissions of China's civil aviation sector in 2019–2020 and the pollutant concentration from the CHAP dataset. Compared to those in 2019, the total NOx, CO, PM, and SO2 emissions during the LTO phase in China's civil aviation sector in 2020 decreased by 14.29%–24.32%, and the average concentrations of NO2, CO, PM10, and SO2 in 2020 decreased by 6.33%–9.45%. The eastern, central, and southern regions of China are characterized by high emissions of pollutants, a phenomenon closely related to the economic prosperity and tourism development in these areas. They tend to boast higher route densities, increasing air transport activity and consequently resulting in elevated emissions. In addition, NOx had the highest correlation coefficient in the empirical model, with a correlation coefficient of 0.603 in 2019. Our findings provide new insights into civil aviation emissions in China from the analysis of the emission inventory of air pollutants and the CHAP dataset and provide a new method for verifying the accuracy and completeness of China's civil aviation emission inventory.

Long-term trends in British Columbia lower mainland air quality: Criteria air pollutants and VOC

ABSTRACT The lower mainland of British Columbia is a geographic region that comprises the districts of Metro Vancouver and the Lower Fraser Valley. It is situated in a complex topographical and coastal location in southwestern British Columbia. Metro Vancouver is Canada’s third largest population center. Accessing the Canadian National Air Pollution Surveillance Program (NAPS) database we calculated air pollutant statistics using the Canadian Ambient Air Quality Standards (CAAQS) averaging times, numerical forms, and numerical levels for the years 2001to 2020. Man Kendall and Sen statistical methods were used to test for the presence of trends and the slope of those trends in fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and volatile organic compound (VOC) ambient air concentrations. We did not determine a significant trend in 98th percentile of the daily 24-hr average PM2.5 concentrations. We did determine significant negative trends in the annual average of the daily 24-hr average PM2.5 concentrations at 6 of the 9 locations. Episodic, multi-day duration elevated PM2.5 concentrations related to forest fires were a significant influence on PM2.5 ambient concentrations. Annual 4th highest daily maximum 8-hr average O3 concentrations showed no trend at 14 of 18 locations, declined at 3 locations, and increased at one location. We determined statistically significant declines in peak and average NO2 and SO2 concentrations, and in time-integrated annual VOC concentrations.

Systematic Review of Sulfur Oxides Levels in Industrial and Urban Settings in Iran

The Sulfur dioxide (SO2) is a prevalent pollutant in urban atmospheres. At a concentration level exceeding 9 ppm, it emits a potent and unpleasant odor and can prove fatal. The most harmful effects of air pollution are often due to a combination of sulfur oxides, particulate matter, and humidity. Given the importance of this pollutant in determining overall air quality, an investigation into its presence in Iranian cities can offer significant insights into the distribution patterns and influencing factors of its concentration levels. Such knowledge is crucial for improving our understanding of air quality and devising effective management strategies. This research was conducted through a systematic review of three databases: Magiran, SID, and Google Scholar. The review focused on articles reporting on the concentration of SO2. A total of 123 articles relevant to the study were initially identified. After a thorough examination, duplicate and irrelevant articles were excluded, leaving 25 articles that fulfilled the inclusion criteria. The analysis shows that the average concentration of SO2 in industrial areas (226.1 ± 218.2 µg/m³) is significantly higher than that in urban areas (92.6 ± 125.4 µg/m³). Furthermore, the concentration of SO2 in outdoor environments (144.2 ± 178.9 µg/m³) exceeds that in indoor environments (74.9 ± 66.9 µg/m³). Notably, the concentration of SOx in central urban areas **surpasses** that in peripheral areas, with an average value of (190.1 ± 144.1µg/m³). The study also found that these concentrations are considerably higher during the summer months, averaging (224 ± 334 µg/m³). The results demonstrate that the levels of sulfur oxides, particularly in industrial settings, are elevated during the warmer seasons in comparison to other periods.

The environmental benefit of tax enforcement: evidence from China

ABSTRACT This study explores how tax enforcement contributes to the improvement of air quality. We leverage the implementation of the Golden Tax Project III in China as a quasi-natural experiment and employ a difference-in-differences framework to establish causality. The findings indicate that the average SO2 concentration in pilot cities decreased by 2.8%, and the average PM2.5 concentration decreased by 3.2%. Further analysis reveals that curbing the expansion of tax-evading firms and ensuring the government’s provision of environmental public goods are mechanisms through which stricter tax enforcement reduces air pollution. These effects are more prominent in cities characterized by a higher proportion of heavy-polluting industries, greater fiscal pressure, and a stronger preference for environmental governance.

Air pollution after acute bronchiolitis is a risk factor for preschool asthma: a nested case-control study

BackgroundAcute bronchiolitis and air pollution are both risk factor of pediatric asthma. This study aimed to assess subsequent exposure to air pollutants related to the inception of preschool asthma in infants with acute bronchiolitis. This study aimed to assess subsequent exposure to air pollutants related to the inception of preschool asthma in infants with acute bronchiolitis.MethodsA nested case-control retrospective study was performed at the Kaohsiung Medical University Hospital systems between 2009 and 2019. The average concentration of PM10, PM2.5, SO2, NO, NO2, and NOX was collected for three, six, and twelve months after the first infected episode. Adjusted regression models were employed to evaluate the association between asthma and air pollution exposure after bronchiolitis.ResultsTwo thousand six hundred thirty-seven children with acute bronchiolitis were included. Exposure to PM10, PM2.5, SO2, NO, NO2, and NOX in the three, six, and twelve months following an episode of bronchiolitis was found to significantly increase the risk of preschool asthma in infants with a history of bronchiolitis.(OR, 95%CI: PM10 = 1.517-1.559, 1.354–1.744; PM2.5 = 2.510-2.603, 2.148–3.061; SO2 = 1.970-2.040, 1.724–2.342; ; NO = 1.915-1.950, 1.647–2.272; NO2 = 1.915-1.950, 1.647–2.272; NOX = 1.752-1.970, 1.508–2.252) In a sensitive analysis of hospitalized infants, only PM10, PM2.5, SO2, and NO were found to have significant effects during all time periods. (OR, 95%CI: PM10 = 1.613-1.650, 1.240–2.140; PM2.5 = 2.208-2.286, 1.568–3.061; SO2 = 1.679-1.622, 1.197–2.292; NO = 1.525-1.557, 1.094–2.181)ConclusionThe presence of ambient PM10, PM2.5, SO2 and NO in the three, six, and twelve months following an episode of acute bronchiolitis has been linked to the development of preschool asthma in infants with a history of acute bronchiolitis.

Statewide assessment of air quality changes in Florida during the COVID-19 pandemic

The COVID-19 pandemic has forced many countries from all over the world to adopt extreme measures to suppress the spread of the pandemic. These measures have triggered changes in air quality. Many studies showed an overall short-term improvement in air quality. This study investigates the long and short-term impacts of COVID-19 pandemic on air quality in the State of Florida. Three air quality indicators (AQI) from 69 stations located in 30 counties in the State of Florida were analyzed for 2015–2021. These pollutants are Fine Particulate Matters (PM2.5), Nitrogen Dioxide (NO2), and Sulfur Dioxide (SO2). The long-term changes in pollutant levels were assessed via Time-Lag linear regression analysis (TLR). The results show that PM2.5 levels dropped from 8.88 to 8.24 μg/m3 between 2015 and 2021. However, the ANCOVA test shows that the TLR's slope for PM2.5 is insignificant, with a p-value of 0.859. Thus, there was no statistical evidence that the changes in 2020 and 2021 differ from previous years. NO2 levels fluctuated over the study period between 13.0 and 16.0 ppm with no identified trend. Nonetheless, the regression slope was also insignificant, with a significance of 0.401. The average SO2 concentrations steadily dropped from 4.3 ppb in 2015 to 2.0 ppb in 2020 and 2.62 ppb in 2021, with a regression slope significance of 0.001. It is concluded that pollutants' levels behave differently during the lockdown and release periods, indicating that the lockdown contribution to reduce industrial activities is reflected on air quality rather than mobile source emissions.

Evaluation of air quality changes in a Chinese megacity over a 15-year period (2006–2021) using PM2.5 receptor modelling

Air quality impairment has a massive impact on human health, with atmospheric particulate matter (PM) playing a major role. The People's Republic of China experienced a trend of increasing PM2.5 concentrations from 2000 to 2013. However, after the application of the Air Pollution Prevention and Control Action Plan and other related control measures, sharp decreases in air pollutant concentrations were particularly evident in the city of Wuhan (central China). This study analysed major changes in PM2.5 concentrations, composition and source apportionment (using receptor modelling) based on Wuhan's PM2.5 chemical speciation datasets from 2006 to 2007, 2019–2021 and contemporaneous gaseous pollutant values. Average SO2 concentrations decreased by 88%, from the first to the second period, mostly due to measures that reduced coal combustion. However, NO2 only declined by 25%, with policy measures likely being undermined by an increased number of vehicles. PM2.5 concentrations decreased by 65%, with the PM constituents each being affected differently. Coal combustion-related element concentrations, OC, SO42−, NH4+, EC, Cl−, Al, Ca, Cu, Fe, Co and NO3− decreased by 22–90%. Secondary inorganic aerosol (SIA) was initially dominated by (NH4)2SO4 (73%) in 2006, but later dominated by NH4NO3 (52%) in 2021. Receptor modelling identified major sources contributing to PM2.5: Mineral, road and desert dust (MRDD), Secondary sulphate (SECS), Secondary nitrate (SECN), Tungsten industry (W), Toxic Elements of Coal (TEC), Iron and Steel (IRONS), Coal Combustion (CC), Residential Heating (RH), Refinery (REF) and Traffic (TRF). In relative proportions, TEC (−83%), SECS (−64%) and SECN (−48%) reduced their contributions to PM2.5 whilst MRDD increased (+62.5%). Thus, the results indicate not only a drastic abatement of PM pollution in Wuhan but also a change in the sources of pollution, which requires further actions to reduce PM2.5 concentrations to health protective values. Secondary PM and fugitive emissions are key components to abate.

Dynamic characteristics of pollutant emissions from CFB boilers during periodic fire banking and start-up

It is difficult to control pollutant emissions during fire banking and start-up in CFB boilers, which poses threats to power plant operation, safety and environmental protection. A 350 MW supercritical CFB boiler was taken as the research object. Using the CPFD method and Barracuda software, a full-loop combustion and pollutant emission model was constructed to simulate periodic fire banking and start-up, and the gassolid flow characteristics and pollutant emission characteristics were analysed. The results showed that the bed material at the bottom of the furnace exhibits obvious stratification after being stationary, and this stratification has an impact on the generation, distribution and emission of NOx and SO2 in the furnace. Eighty-five percent of the bottom bed material is lower layer, and the NOx and SO2 concentrations are negatively correlated with the volume fraction of particles. The average NOx and SO2 concentrations in the lower layer are 120.05 mg/m3 and 1155.50 mg/m3, respectively. During the hot start-up process, the NOx concentration decreases with increasing bed height. The residence time of the desulfurization reaction is prolonged, the desulfurization efficiency is improved, and the SO2 concentration is reduced. These results provide a theoretical basis and a certain reference value for the periodic fire banking and start-up of supercritical CFB boilers.

SPATIO-TEMPORAL VARIABILITY OF AIR QUALITY AND RELATIONSHIP WITH METEOROLOGICAL PARAMETERS IN CAPE TOWN, SOUTH AFRICA

Abstract. African cities are growing fast, and this rapid urbanisation has tremendously increased air pollution and greenhouse gas emissions. Despite this disturbing reality, the deleterious impacts of air pollution on livelihoods and the environment are often overlooked. Recently, the link between air quality and meteorological parameters has received attention from researchers and understanding this relationship could significantly improve our understanding of the spatial and temporal dynamics of air quality. This study focuses on analysing the spatiotemporal variation of three key air quality parameters, namely nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10), in Cape Town between 2020 and 2021. The study also aims to assess the relationship between air quality and meteorological parameters during this period, and the compliance with national and international air quality guidelines. Air quality data were collected from five monitoring stations in the City of Cape Town. A preliminary analysis of the data reveals high increases in the concentration of air pollutants from 2020 to 2021. For instance, the average monthly concentration of NO2 and SO2 at Bellville South station more than doubled during this period (from 6.7–14.8 µg/m3 and 3.4–8.1 µg/m3, respectively). This is worrisome as the air quality index (AQI) exceeded the safe limits at several sites. There is a need for urgent action by national and city governments in Africa to invest in air quality monitoring systems to enhance the well-being of citizens and promote the long-term sustainability of cities and infrastructure.

Comparison of the Air Quality within the Northern Region of India both During and After the Lockdown

The World Health Organization (WHO) declared COVID-19 a global pandemic due to the novel infectious coronavirus disease found in late 2019. Some positive impacts have been seen on the natural environment during the outbreak of COVID-19. In this study, we have tried to analyse the impact of lockdown on air quality at four major northern states of India (Delhi, Uttar Pradesh, Rajasthan, and Haryana) located in the National Capital Region (NCR). This study compared the variation in air pollutants during the first lockdown phase (25th March to 15th April) 2020 and after the lockdown phase (25th March to 15th April) 2022, including PM10, PM2.5, NO2, and SO2. The average concentration of PM10, PM2.5, NO2, and SO2 reduced by 70.43%, 64.7%, 66.37%, and 36.89% over National Capital Region (NCR) during the lockdown phase. A good pollution control plan can lead to significant improvements in air quality in the future, which should provide confidence to policymakers involved in developing air quality policies.

Clearing the Air: Assessing the Effectiveness of Emission Policy in Qinhuangdao’s Key Industries

China has successively put forward ultra-low emission (ULE) transformation plans to reduce the air pollutant emissions of industrial pollutants since 2014. To assess the benefits of the ULE policy on regional air quality for Qinhuangdao, this study developed an emission inventory of nine atmospheric pollutants in 2016 and evaluated the effectiveness of the emission policy in Qinhuangdao’s key industries under different scenarios with an air quality model (CALPUFF). The emissions of air pollutants in 2016 were as follows: Sulfur dioxide (SO2) emitted 48.91 kt/year, nitrogen oxide (NOx) emitted 86.83 kt/year, volatile organic compounds (VOCs) emitted 52.69 kt/year, particulate matter (PM10 and PM2.5) emitted 302.01 and 116.85 kt/year, carbon monoxide (CO) emitted 1208.80 kt/year, ammonia (NH3) emitted 62.87 kt/year, black carbon (BC) emitted 3.79 kt/year, and organic carbon (OC) emitted 2.72 kt/year, respectively. The results showed that at the regional level in 2025, the iron and steel industry under the PPC (Peak Production Capacity) scenario had the highest potential for reducing SO2 and NOx emissions, while the cement industry under the PPC scenario excelled in reducing PM10 emissions. As for the industrial level in 2025, the flat glass industry under the ULE scenario would reduce the most SO2 emitted, while the iron and steel industry and the cement industry under the PPC scenario demonstrated the best reduction in NOx and PM10 emissions, respectively. Furthermore, the average annual contribution concentration of SO2, NOx, and PM10 in the air monitoring stations of Qinhuangdao under the PPC scenario was significantly lower than that under the BAU scenario revealed by air quality simulation. It can be concluded that the emission policy in Qinhuangdao will help improve the air quality. This study can provide scientific support for policymakers to implement the ULE policy in industrial undeveloped cities and tourist cities such as Qinhuangdao in the future.

Studies on the variation in concentrations of respirable suspended particulate matter (PM10), NO2 and SO2 in and around Nagpur

The objective of this study is to assess the long-term variation in concentrations of Respirable suspended particulate matter (PM10), sulphur dioxide (SO2) and nitrogen dioxide (NO2) in the ambient air of Nagpur (India) during 2011-2018. The pollution data during the above period at three locations, viz., residential (Station-I), industrial (Station-II), and commercial location (Station-III) has been analyzed. The highest daily average concentration of PM10 at residential, industrial, and commercial locations was found 154 microgm/m3, 199 microgm/m3, and 153 microgm/m3, whereas, the average annual concentration at these locations was found 101.87 microgm/m3, 115.37 microgm/m3 and 98.75 microgm/m3, respectively during the above period. The highest daily average concentration of SO2 was found at 18 microgm/m3, 22 microgm/m3 and 19 microgm/m3 and the average annual concentration was 13.25 microgm/m3, 13.5 microgm/m3, 13 microgm/m3 at respective locations. And the highest daily average concentration of NO2 was found 77 microgm/m3, 60 microgm/m3, 60 microgm/m3 and the annual average concentration was 44.125 microgm/m3, 41.825 microgm/m3 and 40.25 microgm/m3 at the respective locations. The exceedance factors for PM10 varied from 'moderate to high' at the residential and commercial locations and from 'high to moderate' at the industrial location. Planetary boundary layer height (PBLH) and ventilation coefficient (VC) were also estimated over the region for 2011-2018. The maximum PBLH and VC observed during the study period was in the summer season, and the minimum was in the post-monsoon season. Annual and Seasonal Air quality index analysis shows that the level of pollution was in the range of SATIFACTORY to MODERATE. A study of seasonal analysis of PM10, SO2 and NO2 showed that the higher concentrations were found in winter relative to summer with the least concentration occurring during the monsoon season. A regression analysis was performed to check PM10's interdependence with other contaminants. A positive association was found between PM10 and SO2 for all seasons. A negative association was found between PM10 and NO2 in summer for all the stations and winter at Station-I and Station-III. Similarly, the correlation between PM10 and meteorological parameters such as wind speed and temperature was found to be negative whereas it was positive for relative humidity.

Status of atmospheric air pollution in Ukraine prior to the full-scale russian invasion. Part 1: ground-level content of pollutants

The paper is dedicated to examination of atmospheric air pollution in Ukraine that is aimed at establishing basic air quality conditions prior to the full-scale Russian invasion. Analyses cover five air pollutants (dust, sulfur dioxide (SO2), carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (CH2O)) across 126 monitoring stations in 39 cities. It was found that the most dangerous excess of air pollution levels in cities was associated with dust, NO2, and CO. At the same time, SO2 content usually did not reach dangerous levels. The highest frequency of exceeding the threshold one-time levels was common for the cities with well-developed industrial facilities. Dangerous air pollution was observed in 15–60% of cases, depending on a pollutant. Dust and NO2 concentrations of the most polluted cities were 10 times higher than their concentrations in smaller cities having no significant industrial emissions. The difference in average CO, SO2, and CH2O concentrations among monitoring stations constituted 3-5 times. We studied the patterns of pollutants' seasonal variability recorded at the monitoring stations. Normally, no significant seasonality except for CH2O and dust was observed. The interannual variability of pollutants, emissions, and their trends were analyzed for the period since 2008. We identified a certain discrepancy in trends between pollutants’ concentrations and emission data over the last years. Pollutant content often continued to grow concurrently with emission reductions. The impact of atmospheric phenomena and wind parameters was studied mainly in terms of its role in formation of high and low atmospheric pollution levels. The analysis indicated a crucial role of local conditions in the formation of an atmospheric pollution field next to monitoring stations. Varying atmospheric pollution values across different monitoring stations within a specific city can be different even under the influence of the same atmospheric phenomena. The wind impact also formed different patterns of atmospheric pollution within same city. 12% to 22% of all monitoring stations (depending on a pollutant) indicated a prevailing impact of a single emission source (or a combined impact of a group of sources). At the same time, air pollution at other monitoring stations was highly variable, with elevated pollution levels being transported from numerous directions. The analysis of the air pollution-affected condition presented in the paper could be used as a basis for comparing ground-level pollution and assessing the warfare consequences in Ukraine. The research emphasizes the importance of updating the information about ground-based monitoring stations.

Investigating major sources of air pollution and improving spatiotemporal forecast accuracy using supervised machine learning and a proxy

Because weather can’t be controlled, air pollution can only be managed by planning and controlling the sources. Therefore, mathematical models that do not relate the source to the air quality do not offer guidance on how to regulate the air quality. This is often due to a lack of information about sources or a limited budget to measure emissions from sources that are expected to have a major contribution. A proxy for emission rate was used in modeling to improve the prediction of pollutant concentration and to investigate major sources. The daily average air concentration of NO2 and SO2 were predicted at five different locations using supervised machine learning methods, including random forests and support vector machines regression. Three models were constructed using different combinations of features. In model I, only features relating to the weather were used. Model II used only features of the types and quantities of fossil fuels consumed by power plants, which serve as a proxy for emission rates. In model III, all features from models I and II were used. Model III was found to be the most accurate. The average improvement in R2 for NO2 and SO2 regressions for all sites and using both methods were between 61% and 33%, respectively. This improvement in the prediction indicates that power plants are major sources and contribute significantly to the ambient level of SO2 and NO2 levels. The relative importance of all fuel consumption features was found to be comparable to the value of all weather features. The relative importance values of the fuel consumption features show an opportunity to improve air quality by burning a quantity of fuel in a power plant that has a smaller relative importance value instead. However, whether the receptors are located in rural or urban areas must be considered to maximize the net benefits.