Concentrations Of Atmospheric Pollutants Research Articles

Trend in indices of public health risk caused by air pollution in an industrial center

Introduction. In industrialized regions and cities, atmospheric air pollution greatly contributes to the hazard for public health. The study aim was to assess the state of the atmospheric air in the city of Novokuznetsk over 2017–2022 and determine the levels of risks to public health. Materials and methods. Data on gross atmospheric emissions and average annual concentrations of the substances was taken from the reports on the state of the environment of the Kemerovo region and Novokuznetsk. Maximum permissible concentrations of atmospheric pollutants were determined according to SanPiN 1.2.3685–21. Calculations of the risks to public health were carried out in accordance with Guideline P 2.1.10.1920–04. The classification of risk levels was carried out on the basis of MR 2.1.10.0156–19. 2.1.10. Results. Decrease in total atmospheric emissions from 2017 to 2022 amounted to 50.1 thousand tons (about 16%). At the same time, there was revealed an excess of the average annual maximum permissible concentrations of benzo(a)pyrene (3.5-11.2 times); formaldehyde (1.7 and 3.4 times over 2021 and 2022, respectively); suspended substances (1.6 and 2.0 times in 2021 and 2022, respectively); hydrogen fluoride (1.2 times in 2021); nitrogen dioxide (1.6 times in 2022). The hazard coefficients of benzo(a)pyrene were 3.5–11.2 (high level of non-carcinogenic risk); formaldehyde and suspended substances – 1.1–3.0 (alarming level). In 2022, the hazard coefficient for formaldehyde was 3.4 (high risk level), suspended substances – 2.0, nitrogen dioxide – 1.6 (alarming risk level). Hazard indices of pollutants were detected in the range from 7.0 to 20.1 (high level of risk). The main critical organs and systems were the immune system (hazard indices were 4.0–14.6), development during childhood (hazard indices – 3.5–11.2), respiratory organs (hazard indices – 3.0–8.6). These risk levels range from alarming to high. The highest total individual carcinogenic risk (1.6•10–4) was determined in 2021 (alarming level), the main contribution is made by formaldehyde. Limitations. In 2022, there were no data on carbon (soot) concentrations, so the level of total carcinogenic risk this year cannot be considered to be correct. Conclusion. Reducing the total volume of atmospheric emissions does not provide a significant effect on improving the environmental situation and public health, since high concentrations of pollutants remain in the city’s atmosphere. When implementing air protection measures, it is necessary to take into account risk criteria.

Observational study of major air pollutants over urban Romania in 2020 in comparison with 2019

This study aims to characterize urban air pollution in 33 cities across Romania in 2019 and 2020. The global COVID-19 pandemic that started in mid-March 2020 provided us with a unique opportunity to find out what would be the possible variation range of major air pollutants in Romanian urban areas under various strengths of anthropogenic activity. The time-series of atmospheric main pollutant mass concentrations, particulates PM10 and PM2.5 and gaseous species NO2, CO, SO2, O3, were statistically analyzed for each city for the representative month of each season in 2019 and 2020 and then used to estimate the pollutant impact on the surrounding regions. Results show significant decreases for most pollutants in most cities especially in spring of 2020, during the hard lockdown period. Maps of interpolated mass concentrations reveal regional significant differences with pollutant-specific hot- and cold-spots in Romania. This work constitutes a good database to characterize de urban air pollution in Romanian major cities and the spatial distribution of their impact around.

Ozone Pollution in Suzhou During Early Summertime: Formation Mechanism and Interannual Variation

This study investigated the concentrations of atmospheric pollutants in the urban area of Suzhou from May to June, 2017-2021. The variation characteristics and annual changes of ozone (O3), nitrogen oxide (NOx), total oxidant (Ox), carbon monoxide (CO), and volatile organic compounds (VOCs) were analyzed. The O3 formation mechanism and its annual changes were studied using an Observation-Based Model (OBM), and VOCs source apportionments and their trends were discussed. The results indicated that ① The volume fractions of Ox and the concentrations of NOx and CO have decreased in the urban area of Suzhou in recent years, while the volume fractions of VOCs have increased, and sufficient photochemical conditions for O3 formation still existed during polluted days. ② The O3-NOx-VOCs sensitivity in Suzhou was in the VOCs-limited regime. The long-term reduction ratio between VOCs and NOx should not be less than 5:1, and aromatics and alkenes were the critical VOCs for mitigating O3 pollution. ③ The results of VOCs source apportionment revealed that industrial emissions, gasoline vehicle exhaust, and diesel engine exhaust were the major sources of VOC emissions in Suzhou. Industrial emissions and solvent usage declined from 2017 to 2021; however, gasoline vehicle exhaust and gasoline evaporation, which possess higher O3 formation potential(OFP), increased significantly. ④ The OFP source apportionments results indicated that controlling VOC emissions from solvent usage and gasoline vehicle exhaust is crucial for O3 pollution control in Suzhou.

Effects of chemical mechanism and meteorological factors on the concentration of atmospheric pollutants in the megacity Beijing, China

To distinguish the effects of chemical mechanisms and meteorological factors on air pollution in the megacity of Beijing, the sensitive numerical experiments with the third-generation air quality modeling system (WRF-SMOKE-CMAQ) are designed for a one-year simulation in 2018. The results indicate that: 1) the modeling system plays well in performance in the megacity of Beijing in 2018. The correlation coefficient of the simulated PM2.5 concentration and the observation value reaches 0.74, while the normal mean bias is −14%–32% in the National Standard Air Quality observation stations in Beijing. 2) The impact of chemical mechanisms on pollutants such as ANO3 is significant, reaching 1075%. However, there is almost no impact on AEC, or ASO4 from the chemical mechanisms. The impact of chemical mechanisms on NO and O3 concentration is between the aforementioned two, with a relatively small degree of impact. The influence of chemical mechanisms on PM2.5 concentration is 35%, while the meteorological factors are 65% under the experiments. 3) For the photochemical species, the peak frequencies of NO2 concentration in the two experiments are 27.1 ppbV and 5.9 ppbV, respectively, and the peak frequency of NO2 observed concentration is 19.1 ppbV, near to the simulation in the baseline group, which illustrates that the chemical mechanism includes a large amount of NO2 generation. The numerical model is a good tool to quantify the effect of chemical mechanisms and meteorological factors. In addition, the concentration of NO2 in Beijing is decreasing from urban to exurb areas in terms of spatial distribution, and the spatial variation of PM2.5 is also the same.

Spatio-temporal data prediction of multiple air pollutants in multi-cities based on 4D digraph convolutional neural network.

In response to the problem that current multi-city multi-pollutant prediction methods based on one-dimensional undirected graph neural network models cannot accurately reflect the two-dimensional spatial correlations and directedness, this study proposes a four-dimensional directed graph model that can capture the two-dimensional spatial directed information and node correlation information related to multiple factors, as well as extract temporal correlation information at different times. Firstly, A four-dimensional directed GCN model with directed information graph in two-dimensional space was established based on the geographical location of the city. Secondly, Spectral decomposition and tensor operations were then applied to the two-dimensional directed information graph to obtain the graph Fourier coefficients and graph Fourier basis. Thirdly, the graph filter of the four-dimensional directed GCN model was further improved and optimized. Finally, an LSTM network architecture was introduced to construct the four-dimensional directed GCN-LSTM model for synchronous extraction of spatio-temporal information and prediction of atmospheric pollutant concentrations. The study uses the 2020 atmospheric six-parameter data of the Taihu Lake city cluster and applies canonical correlation analysis to confirm the data's temporal, spatial, and multi-factor correlations. Through experimentation, it is verified that the proposed 4D-DGCN-LSTM model achieves a MAE reduction of 1.12%, 4.91%, 5.62%, and 11.67% compared with the 4D-DGCN, GCN-LSTM, GCN, and LSTM models, respectively, indicating the good performance of the 4D-DGCN-LSTM model in predicting multiple types of atmospheric pollutants in various cities.

Vehicular Volume and Concentration of Gaseous Atmospheric Pollutants and Particulate Matter at Selected Road Junctions in Port Harcourt, Nigeria

The increase in industrial and vehicular activities has led to the proliferation of atmospheric pollutants in cities globally. The Niger Delta region is an industrial hub and serves as the nation's resource base by exploring crude oil. This work postulated that there would be high pollutants and particulate matter at road junctions due to the multiplicity of several vehicles owned by the surging human population. The number of vehicles at each junction were counted. A multi-parameter gas monitor (A multi–RAE PLUS (PGM-50) was used to collect air samples at different junctions (n = 5). The concentration of nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter (PM2.5, PM10), temperature, relative humidity, and wind were analyzed. The result revealed that the volume of the vehicles at road traffic junctions follows the order Rumuola>Mile 3/UST Roundabout>Choba Junction>Garrison>Lagos Bus Stop. Choba Junction had the highest concentration of pollutants. The highest concentration of vehicular pollutants was observed in the morning. Carbon monoxide (CO) had the highest concentration, followed by SO2 and NO2. While for particulate matter, PM2.5 had a higher concentration than PM10. The result implies that the number of vehicular traffic does not necessarily determine the concentration of pollutants because other anthropogenic activities are causing a spike in atmospheric pollutants within the city.

Impacts of maritime shipping on air pollution along the US East Coast

Abstract. Air pollution is considered a leading threat to human health in the US and worldwide. An important source of air pollution in coastal areas is the globally increasing maritime shipping traffic. In this study, we take a high-resolution modeling approach to investigate the impacts of ship emissions on concentrations of various atmospheric pollutants, under the meteorological conditions and emissions of the year 2018. We utilize the Comprehensive Air Quality Model with extensions (CAMx) to simulate transport, diffusion, and chemical reactions and the Weather Research and Forecasting (WRF) model to provide the meteorological inputs. We focus on four criteria pollutants – fine particulate matter with a diameter smaller than 2.5 µm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) – as well as nitrogen oxide (NO), and we calculate their concentrations in the presence and absence of ship emissions along the US East Coast, particularly in the proximity of major ports. We find that ship emissions increase the PM2.5 concentrations over the ocean and over a few areas inland. The 98th percentile of the 24 h average PM2.5 concentrations (the “design value” used by the US Environmental Protection Agency) increased by up to 3.2 µg m−3 in some coastal areas. In addition, ships contribute significantly to SO2 concentrations, up to 95 % over the Atlantic and up to 90 % over land in coastal states, which represents a ∼45 ppb increase in the SO2 design values in some states. The 98th percentile of the hourly NO2 concentrations also increased by up to 15 ppb at the major ports and along the shore. In addition, we find that the impact of shipping emissions on O3 concentrations is not uniform, meaning that ships affect ozone pollution in both positive and negative ways: over the ocean, O3 concentrations were significantly higher in the presence of ships, whereas O3 concentrations decreased in the presence of ships in major coastal cities. Our simulation results show that ships emit significant amounts of fresh NO in the atmosphere, which then helps scavenge O3 in volatile organic compound (VOC)-limited areas, such as major ports. By contrast, over the ocean (NOx-limited regime), enhanced NOx concentrations due to ships contribute to the formation of O3 and therefore enhance O3 concentrations. Overall, due to the dominant southwesterly wind direction in the region, the impacts of ships on air pollutants mainly remain offshore. However, in coastal states near major ports, the impacts are significantly important.

Study on the changes in concentration of air pollutants and influencing factors in road green spaces in Nanjing City during autumn and winter

Based on low-altitude remote sensing of UAV and field monitoring on three roads in Nanjing, this study used the normalized difference vegetation index (NDVI) one-dimensional linear regression analysis, correlation analysis to explore the relationship between different influencing factors and concentration changes of different pollutants in autumn and winter. The results showed that: 1. The use of UAV low-altitude remote sensing to collect vegetation data at road scale coould reflect the change characteristics of road vegetation in autumn and winter, especially the proportion of deciduous plants: among three roads, the ratio of deciduous plants to road sections showed that Mengdu Street < Mufu South Road < Jiyin Avenue; 2. Seasonal variation had a significant effect on temperature. In autumn, the concentration of NO2 in Jiyin Avenue and Mufu South Road exceeded the standard limit of 24 h average level 2 concentration, which meant the air pollution was relatively serious. 3. The increase of NDVI could reduce the concentration of atmospheric pollutants. Also, the study found that humidity had the greatest correlation with PM2.5 and PM10, temperature had the greatest correlation with NO2 and air pressure had the greatest correlation with O3. In addition, the four pollutants had positive correlation with each other.

Atmospheric Pollutant Dispersion Modeling Methods

Abstract The method of modeling and simulating different phenomena in various fields of scientific knowledge is an essential part of many branches of science, each of which has specific types of models. Using mathematical methods, these models try to simulate a real situation by means of numerical analysis that describes the relationships between the characteristic quantities of air pollution phenomena, such as emissions, meteorology atmospheric concentrations of pollutants, deposition, and other factors. Air and water pollution measurements give information about the environmental concentrations of pollutants scattered by different sources but can only describe the phenomena involved qualitatively, at specific locations and times, without identifying the causes that lead to pollution problems. However, models of air and groundwater pollution can provide a deterministic description of the problems of air or water quality, including an analysis of the factors and causes of the pollution phenomenon (emission sources, meteorological processes and chemical and physical changes), and some guidance for implementing measures to mitigate these phenomena of environmental pollution. Due to the ability of these methods to establish the relative importance of relevant processes, they play an important role in current day science.

NO2 Concentration Estimation at Urban Ground Level by Integrating Sentinel 5P Data and ERA5 Using Machine Learning: The Milan (Italy) Case Study

The measurement of atmospheric NO2 pollution concentrations has become a critical topic due to its impact on human health. Ground sensors are the most popular method for measuring atmospheric pollution, but they can be expensive to purchase, install, and maintain. In contrast, satellite technology offers global coverage but typically provides concentration estimates at the tropospheric level, not at the ground level where most human activities take place. This work presents a model that can be used to estimate NO2 ground-level concentrations in metropolitan areas using Sentinel-5P satellite images and ERA5 meteorological data. The primary goal is to offer a cost-effective solution for Low- and Medium-Income Countries (LMICs) to assess air quality, thereby addressing the air quality measurement constraints. To validate the model’s accuracy, study points were selected in alignment with the Regional Agency for the Environment Protection (ARPA) NO2 sensor network in the Metropolitan City of Milan. The results showed that the RMSE of the model estimations was significantly lower than the standard deviation of the real measurements. This work fills the gaps in the literature by providing an accurate estimation model of NO2 in the Metropolitan City of Milan using both satellite data and ERA5 meteorological data. This work presents as an alternative to ground sensors by enabling more regions to assess their air quality effectively.

Rapid reduction of air pollution and short-term exposure risks in China

With the continuous control of anthropogenic emissions, China's air quality has improved significantly in recent years. Given this background, research on how the short-term exposure risks caused by air pollution in China have changed is insufficient. This study utilized hourly concentration data from ground observation stations and the official air quality guidelines of the Ministry of Ecology and Environment of China and the World Health Organization as standards to systematically investigate the spatiotemporal characteristics and short-term exposure risks of air pollution in China from 2015 to 2022. The results indicate that various atmospheric pollutants except for ozone showed a decreasing trend yearly. Nationwide, both single pollutant air pollution days (SAPDs) and multiple pollutant air pollution days (MAPDs) showed varying degrees of reduction within 15 and 25 days, respectively. SAPD was dominated mainly by excessive PM2.5 and PM10 pollutants, while MAPD was dominated mainly by excessive pollutant combinations, including PM2.5 + PM10, CO + PM2.5 + PM10, and SO2 + PM2.5 + PM10. As the concentration of atmospheric pollutants decreased, the total excess risk (ER) decreased yearly from 2015 to 2022, but there were significant regional differences. Now, the ER is less than 0.25% in southern China, in the range of 0.25%-0.5% in the North China Plain and some cities in the northeast, and higher than 1% in the northwest. Particulate matter is currently the primary pollutant posing short-term exposure risk in China, especially due to the impact of sandstorm weather. This study indicates that China's atmospheric cleaning action is significantly beneficial for reducing health risks.

Impact of air pollution on mortality: geo-epidemiological study in French-speaking Africa

Abstract According to the WHO, air pollution is responsible for 90% of deaths in Africa. However, few data on exposure to air pollution is available, and studies are rare, particularly in French-speaking Africa. This study aims to investigate the impact of air pollution on mortality in 13 French-speaking African countries (Algeria, Benin, Burkina Faso, Burundi, Cameroon, Ivory Coast, Guinea, Madagascar, Mali, Morocco, Democratic Republic of Congo, Senegal, Tunisia). Using data from the IHME, annual concentrations of the PM2.5 pollutant from different cities were integrated into a spatial interpolation model (IDW) at the scale of each country. The interpolation was validated using cross-validation models. For each of the considered cardiorespiratory diseases (LRI, stroke, COPD, IHD), the attributable mortality fraction was estimated using literature data and population exposure calculated using demographic data from each country. Large variations in concentration between the 13 countries are observed, with concentrations ranging from 1.76µg/m3 in Morocco to 67.03µg/m3 in Benin. Concentrations are higher in West Africa than in Central or North Africa. In 2019, 291,417 deaths attributable to air pollution were recorded in the 13 countries: 19.7% for ischemic heart disease, 6.5% for lower respiratory infections, 3.6% for chronic obstructive pulmonary disease, and 18.8% for stroke. Our model allowed us to obtain a spatial distribution and the number of deaths related to air pollution. However, the health impact of pollution could be improved by more systematic and comprehensive data collection through a system for monitoring concentrations of atmospheric pollutants. Key messages • This study estimates the number of deaths attributable to air pollution in 13 French-speaking African countries using a spatial interpolation model. • This study highlights the need for more data on air pollution exposure in French-speaking Africa.

Temporal Analysis of Atmospheric Pollutant Concentrations with Specific Regard to NAAQS Compliance in an Industrial Cluster of New Delhi, India

Temporal Analysis of Atmospheric Pollutant Concentrations with Specific Regard to NAAQS Compliance in an Industrial Cluster of New Delhi, India

A review of international experience in air quality assessment

This article provides a comprehensive overview of global practices in assessing atmospheric air quality in different countries. The review is based on scientific literature, regulatory frameworks, and methodological documents. It delves into the specificities of pollutant regulation in various countries, including Russia, and compares the standards established in each. Substantial differences in the approaches to the regulation of pollutants in the atmospheric have been identified between the countries.&#x0D; Furthermore, this study examines the methods for assessing air quality and instrumental control. It explores renowned mathematical models used for evaluating and predicting atmospheric air quality. Notably, the findings reveal striking similarities between data obtained through predictive modeling and field measurements. However, the utilization of an extensive network of measurement stations enables the acquisition of the most precise and up-to-date information on atmospheric pollutant concentrations.&#x0D; Moreover, this article offers an overview of online services available globally for real-time monitoring of atmospheric air quality. These platforms play a crucial role in providing immediate insights into the state of the air we breathe. Additionally, the article presents the methods employed for assessing the health risks associated with atmospheric pollutant levels and their impact on the population health.&#x0D; It has been established that the countries of Europe, the USA, and China have achieved significant success in the field of atmospheric air quality control. Residents in these countries have access to up-to-date information about the state of atmospheric air in real-time. However, in Russia, despite ongoing assessments of air quality, there is currently no public service available that provides comprehensive information on atmospheric air quality.

Investigation of the impact mechanisms and patterns of meteorological factors on air quality and atmospheric pollutant concentrations during extreme weather events in Zhengzhou city, Henan Province

Quantitative analysis of the complex relationships between meteorological factors and atmospheric pollution under extreme weather conditions is of crucial importance for future climate change assessment and air pollution control policy implementation. In this study, we used a multi-factor generalized additive model (MGAM) to investigate the nonlinear interaction between meteorological factors and atmospheric pollutants during the “7–20″ extreme precipitation event (EP) in 2021 and the heat wave event (EH) in June 2022 in Zhengzhou City. The results showed that atmospheric pollutant concentrations decreased significantly (p < 0.05) relative to the baseline concentrations during the study period. EH events usually have lower humidity than EP events, so the negative effects of precipitation and relative humidity on pollutant concentrations were significantly higher during the EP than during the EH. In contrast, the effect of temperature on O3 concentration was significantly higher than that on other pollutants during the EH. The results of MGAM indicated the changes in pollutant concentrations were significantly nonlinearly influenced by multiple meteorological factors, both during the EP and EH periods. During the EP, O3 concentration peaked when relative humidity was below 70% and temperature was around 26 °C, and PM2.5 concentration was highest when relative humidity was about 80% and hourly precipitation was below 50 mm. During the EH, high temperature (>35 °C) and lower relative humidity (<35%) aggravated atmospheric pollution. Meanwhile, we found that O3 concentration peaked in when relative humidity was below 20% and temperature reached 40 °C. In addition, there was temporal heterogeneity in the interaction effects of different meteorological factors on atmospheric pollutants during the EP and EH. Our findings have implications for the continued implementation of stringent local air quality policies and the adoption of effective air pollution prevention and control measures.

Primary sources of HONO vary during the daytime: Insights based on a field campaign

Nitrous acid (HONO) is an established precursor of hydroxyl (OH) radical and has significant impacts on the formation of PM2.5 and O3. Despite extensive research on HONO observation in recent years, knowledge regarding its sources and sinks in urban areas remains inadequate. In this study, we monitored the atmospheric concentrations of HONO and related pollutants, including gaseous nitric acid and particulate nitrate, simultaneously at a supersite in downtown Chengdu, a megacity in southwestern China during spring, when was chosen due to its tolerance for both PM2.5 and O3 pollution. Furthermore, we employed the random forest model to fill the missing data of HONO, which exhibited good predictive performance (R2 = 0.96, RMSE = 0.36 ppbv). During this campaign, the average mixing ratio of HONO was measured to be 1.0 ± 0.7 ppbv. Notably, during periods of high O3 and PM2.5 concentrations, the mixing ratio of HONO was >50 % higher compared to the clean period. We developed a comprehensive parameterization scheme for the HONO budget, and it performed well in simulating diurnal variations of HONO. Based on the HONO budget analysis, we identified different mechanisms that dominate HONO formation at different times of the day. Vehicle emissions and NO2 heterogeneous conversions were found to be the primary sources of HONO during nighttime (21.0 %, 30.2 %, respectively, from 18:00 to 7:00 the next day). In the morning (7:00–12:00), NO2 heterogeneous conversions and the reaction of NO with OH became the main sources (35.0 %, 32.2 %, respectively). However, in the afternoon (12:00–18:00), the heterogeneous photolysis of HNO3 on PM2.5 was identified as the most substantial source of HONO (contributing 52.5 %). This study highlights the significant variations in primary HONO sources throughout the day.

Exposure to Air Pollution in Transport Microenvironments

People spend approximately 90% of their day in confined spaces (at home, work, school or in transit). During these periods, exposure to high concentrations of atmospheric pollutants can pose serious health risks, particularly to the respiratory system. The objective of this paper is to define a framework of the existing literature on the assessment of air quality in various transport microenvironments. A total of 297 papers, published from 2002 to 2021, were analyzed with respect to the type of transport microenvironments, the pollutants monitored, the concentrations measured and the sampling methods adopted. The analysis emphasizes the increasing interest in this topic, particularly regarding the evaluation of exposure in moving cars and buses. It specifically focuses on the exposure of occupants to atmospheric particulate matter (PM) and total volatile organic compounds (TVOCs). Concentrations of these pollutants can reach several hundreds of µg/m3 in some cases, significantly exceeding the recommended levels. The findings presented in this paper serve as a valuable resource for urban planners and decision-makers in formulating effective urban policies.

Environmental science through orbiters. An example of Sentinel-5P on how the Covid-19 pandemic impacted the air quality

Due to the lockdown caused by the SARS-CoV-2 coronavirus disease (a.k.a. COVID-19) pandemic in 2020, most industrial and social activity drastically stopped. This drastic fall in human and industrial activity might have caused a drastic fall in the concentration of important atmospheric pollutants. This study investigates whether the atmospheric concentration of NO2, CO, HCOOH, CH4, SO2 and O3 changed during this extraordinary situation. Secondly, this manuscript demonstrates how orbiter data can be freely used to endeavour any research question and the usefulness of multivariate data analysis in analyzing such data. The data used was the European Space Agency Copernicus Sentinel-5P satellite (SP5). Besides, the molecular concentration found with S5P was compared with the ground meteorological stations of the Basque Government, Spain. Concerning the individual evolution of the molecular concentrations found with SP5, no significant differences were obtained for the abovementioned molecules for the same period (from January until June) in different years (2019 and 2020) using ANOVA. The average concentration between years and their respective relative standard deviations were in the same range. Nevertheless, Principal Component Analysis applied to the time series demonstrated significant changes in the overall behaviour of the monitored pollutants.

Atmospheric Pollution in Port Cities

Authoritative, trustworthy, continual, automatic hourly air quality monitoring is a relatively recent innovation. The task of reliably identifying long-term trends in air quality is therefore very challenging, as well as complex. Ports are major sources of atmospheric pollution, which is linked to marine traffic and increased road traffic congestion. This study investigated the long-term trends and drivers of atmospheric pollution in the port cities of Houston, London, and Southampton in 2000–2019. Authoritative air quality and meteorological data for seven sites at these three locations were meticulously selected alongside available traffic count data. Data were acquired for sites close to the port and sites that were near the city centre to determine whether the port emissions were influencing different parts of the city. Openair software was used for plots and statistical analyses. Pollutant concentrations at Houston, Southampton and Thurrock (London) slowly reduced over time and did not exceed national limits, in contrast to NO2 and PM10 concentrations at London Marylebone Road. Drivers of atmospheric pollution include meteorology, geographical and temporal variation, and traffic flow. Statistically significant relationships (p &lt; 0.001) between atmospheric pollution concentration and meteorology across most sites were found, but this was not seen with traffic flows in London and Southampton. However, port emissions and the other drivers of atmospheric pollution act together to govern the air quality in the city.

Sources, sinks, and chemistry of Stabilized Criegee Intermediates in the Indo-Gangetic Plain

Night-time oxidation significantly affects the atmospheric concentration of primary and secondary air pollutants but is poorly constrained over South Asia. Here, using a comprehensively measured and unprecedented set of precursors and sinks of Stabilized Criegee Intermediates (SCI), in the summertime air of the Indo-Gangetic Plain (IGP), we investigate the chemistry, and abundance in detail. This study reports the first summertime levels from the IGP of ethene, propene, 1-butene, cis-2-butene, trans-2-butene, 1-pentene, cis-2-pentene, trans-2-pentene, and 1-hexene and their possible roles in SCI chemistry. Ethene, propene, and 1-butene were the highest ambient alkenes in both the summer and winter seasons. Applying chemical steady-state to the measured precursors, the average calculated SCI concentrations were 4.4 (±3.6) × 103 molecules cm−3, with Z-CH3CHOO (55 %) as the major SCI. Z-RCHOO (35 %) and α-pinene derived PINOO (34 %) were identified as the largest contributors to SCI with a 7.8 × 105 molecules cm−3 s−1 production rate. The peak SCI occurred during the evenings. For all SCI species, the loss was dominated (>50 %) by unimolecular decomposition or reactions with water vapor or water vapor dimer. Pollution events influenced by crop burning resulted in significantly elevated SCI production (2.1 times higher relative to non-polluted periods) reaching as high as (7.4 ± 2.5) × 105 molecules cm−3 s−1. Among individual SCI species, Z-CH3CHOO was highest in all the plume events measured accounting for at least ~41 %. Among alkenes, trans-2-butene was the highest contributor to P(SCI) in plume events ranging from 22 to 32 %. SCIs dominated the night-time oxidation of sulfur dioxide with rates as high as 1.4 (±1.1) × 104 molecules cm−3 s−1 at midnight, suggesting that this oxidation pathway could be a significant source of fine mode sulfate aerosols over the Indo-Gangetic Plain, especially during summertime biomass burning pollution episodes.