Daily Pollution Research Articles

Identifying spatio-temporal climatic characteristics and events of the South-Asian aerosol pollution transport to the Tibetan Plateau

South Asian aerosol pollutants can be transported to the Tibetan Plateau (TP) and affect the local atmospheric environment; however, few studies have produced statistical results for the long term. In this study, 41 years of pollution transport events from South Asia to the TP were screened based on Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data using objective methods, and the main pollution transport mechanisms were revealed. We used the empirical orthogonal functions (EOF) and the rotated empirical orthogonal functions (REOF) methods to obtain the spatiotemporal variation characteristics of the aerosol optical depth (AOD) over the TP and the large loading regions of AOD variation from 1980 to 2020 and combined them with the backward trajectory to screen for severe pollution events in the TP influenced by transport from South Asia. The three regions (eastern, central and western regions) with large AOD loading variations in the southern TP are shown by the REOF. Based on the objectively defined AOD indices for the three regions, 2058 days of strong pollution were identified, of which 1702 days (82.7%) were affected by pollution transport from South Asia. Of these 1702 days, the central region had the highest number of days at 661 (38.8%), followed by the western and eastern regions with 544 (32%) and 497 (29.2%) days, respectively. The results obtained from the transport events in the three regions suggest that South Asian pollutants can be transported across the Himalayas to the TP by valley winds, north-south valley passages, and cyclonic uplift. These findings deepen the understanding of the aerosol pollution of the TP affected by pollution transport from South Asia.

Fast spreading of surface ozone in both temporal and spatial scale in Pearl River Delta

Surface ozone (O3) is a major air pollutant and draw increasing attention in the Pearl River Delta (PRD), China. Here, we characterize the spatial-temporal variability of ozone based on a dataset obtained from 57 national monitoring sites during 2013-2019. Our results show that: (1) the seasonal difference of ozone distribution in the inland and coastal areas was significant, which was largely affected by the wind pattern reversals related to the East Asian monsoon, and local ozone production and destruction; (2) the daily maximum 8hr average (MDA8 O3) showed an overall upward trend by 1.11 ppbv/year. While the trends in the nine cities varied differently by ranging from -0.12 to 2.51 ppbv/year. The hot spots of ozone were spreading to southwestern areas from the central areas since 2016. And ozone is becoming a year-round air pollution problem with the pollution season extending to winter and spring in PRD region. (3) at the central and southwestern PRD cities, the percentage of exceedance days from the continuous type (defined as ≥3 days) was increasing. Furthermore, the ozone concentration of continuous type was much higher than that of scattered exceedance type (<3 days). In addition, although the occurrence of continuous type starts to decline since 2017, the total number of exceedance days during the continuous type is increasing. These results indicate that it is more difficult to eliminate the continuous exceedance than the scatter pollution days and highlight the great challenge in mitigation of O3 pollution in these cities.

Impact of primary emission variations on secondary inorganic aerosol formation: Prospective from COVID-19 lockdown in a typical northern China city

Hourly observations in northern China city of Taiyuan were performed to compare secondary inorganic aerosol (SIA) reaction mechanisms, and emission effects on SIA during the pre-lock and COVID-19 lock days. Emission control implemented and meteorological conditions during lock days both caused beneficial impact on air quality. NO2 showed the highest decrease ratio of −49.5%, while the relative fraction of NO3− in PM2.5 increased the most (2.7%). Source apportionment revealed the top three contributors to PM2.5 were secondary formation (SF), coal combustion (CC), and vehicle exhaust (VE) during both pre-lock and lock days. EC lock/pre were all lower than 1, suggesting the overall reduction of primary emissions during lock days, while the higher ratio of (SIA/EC) lock/pre (1.01–1.36) indicated the enhanced secondary formation in lock days. The ratio of SIA of pollution to clean days during lock periods considerably higher by 23.7% compared with that in pre-lock periods, which was indicated SIA secondary formation was more pronounced and contributed great to pollution days in lock periods though secondary formation existed in pre-lock and lock periods. Enhanced secondary formation of NO3− and SO42− during lock days might be mainly due to the increased in aqueous and gas-phase reactions, respectively. Except for SF, high contribution of VE and CC were also important for high SIA concentration in pre-lock and lock days, respectively. The decreased contribution of VE weakens its contribution to SIA formation, indicating the effectiveness of VE emission control, as confirmed during the COVID-19 pandemic. This study highlights the aqueous and gas-phase reactions for nitrate and sulfate, respectively, which contributed to heavy pollution, as well as indicated the important role of VE on SIA formation, suggesting the urgent need to further strengthen controls on vehicle emissions.

Health effects of exposure to particulate matter and physical activity by individual sustainable commuting modes

Promotion of sustainable commuting modes (e.g., walking, cycling and electric mobility) is considered as a promising solution to achieve sustainability. Active travel may also increase physical activity, which is beneficial for health. But it increases health burdens by directly exposing commuters to air pollution. There is a lack of generalizable quantitative approaches to comprehensively evaluate the health outcomes of sustainable plans during the design period. In this research, we aim to examine the long-term combined health impacts of commuting by walking, cycling, and e-moped in Cangzhou, China, a populous industrial city with high air pollution levels, to inform decision-making prior to the implementation of sustainable strategies. A taxi-based mobile remote sensing system was implemented to create a link-level fine particulate matter (PM2.5) concentration map to overcome the insufficiency of sparse fixing monitoring network, which allows researchers to determine joint relative risks of all-cause mortality at a finer spatial scale. Results show that the benefits always outweighed the risks for active commuting at the case study site, even in high polluted days. E-moped commuters experienced a negative burden. In our case, encouraging these commuters to travel during off-peak periods to reduce exposure might not be effective and could even lead to greater PM2.5 exposure than during peak periods (up to 0.37 μg/km). The proposed method can be applied to different locations, providing decision makers with the information needed to target interventions to achieve sustainability.

Ambient VOCs Characteristics and Reactivity During O3 Pollution in Autumn in Urban Beijing

In order to understand the effect of volatile organic compounds (VOCs) on ozone pollution, the concentrations, chemical composition variations, and ozone formation potential (OFP) were studied under different O3 concentrations, using high-resolution online monitoring data obtained in the urban site of Beijing in autumn of 2019. The results showed that the average concentration of VOCs was (22.22±10.10)×10-9, with the largest contribution of VOCs from alkanes (55.65%), followed by that of oxygenated volatile organic compounds (OVOCs) (16.23%) and alkenes (8.13%). Three ozone pollution episodes were captured during the observation period. The average concentration of VOCs on pollution days was (26.22±12.52)×10-9, which was 60.17%higher than that on clear days (16.37±7.19)×10-9. The value of ozone formation potential (OFP) on pollution days was 113.63 μg·m-3, which was 56.55%higher than that on clear days. The contributions of OVOCs and aromatics to OFP on pollution days increased by 6.51%and 1.55%, respectively, whereas that of alkenes declined (8.72%). The ratios of toluene to benzene (T/B) and benzene, toluene, and ethylbenzene (B:T:E) were 1.55 and 0.36:0.55:0.09, respectively, indicating that vehicle exhaust had significant effects on VOCs in autumn in urban Beijing. The back-trajectory results indicated a high contribution of southern air masses to atmospheric VOCs variations in autumn in urban Beijing.

Meteorological Characteristics, Influence Analysis and Prediction of PM2.5 Concentration in Taiyuan City

Based on the pollutant concentration data of Taiyuan City from 2016 to 2020 and the surface meteorological data of the national benchmark meteorological observation station in the same period, the variation characteristics of PM2.5 concentration in Taiyuan City and the effects of meteorological conditions such as humidity, precipitation, wind, and mixing layer thickness on PM2.5 concentration were analyzed. At the same time, the causes of pollutant concentration changes were discussed, and the PM2.5 concentration prediction model based on the LSTM neural network was established. The results showed that the number of days of heavy pollution in Taiyuan City from 2016 to 2020 was the highest in winter, of which the maximum number of days in 2017 was 28 days. The PM2.5 concentration was generally high in autumn and winter and low in spring and summer. The PM2.5 concentration on weekends was higher than that on weekdays. The daily variation in PM2.5 concentration roughly presented a bimodal distribution, which appeared around 09:00 and 23:00 to 01:00 the following day. Except for relative humidity and winter temperature, other air pressure, wind speed, and PM concentration showed negative correlations in the four seasons. The pollution sources affecting the increase in PM2.5 concentration in Taiyuan City were mainly located in the NE-ENE-E direction, and the pollution in the northwest was not relatively apparent. In flood season, when the precipitation reached the level of moderate rain (rainfall ≥ 10 mm), it had an obvious effect on the reduction of PM2.5 concentration. The increase in atmospheric mixing layer height was very beneficial to the diffusion and dilution of PM2.5 in the vertical direction. The strong northwest air flow in winter, low relative humidity, high pressure control on the ground, and high height of the mixing layer belonged to the cluster most conducive to the reduction in PM2.5 concentration. Using the LSTM model for modeling, the R2 of PM2.5 concentration prediction was as high as 0.95, which was significantly better than that of the traditional tree model and linear regression model (R2<0.60). The residual of the prediction results was close to the normal distribution, of which the absolute error of 84.2% prediction results was less than 20 μg·m-3, and the MAE, MAPE, and RMSE of the model were 38.17, 17.19%, and 20.6, respectively.

Air pollution mitigation in North China through flexible heating policies

Central heating in North China produces severe air pollution, although the need for heating may be reduced by rising temperatures associated with climate change. The regional trend of mean heating length (HL) for North China was −0.32 d per year during 1961–2019. Compared with the 2010–2015 mean values, the start and end dates for central heating in the North China Plain (NCP) during 2050–2055 will delayed by 9 d and advanced by 12 d, respectively, under the Shared Socioeconomic Pathway 5–8.5 (SSP5-85), and by 5 and 8 d under the carbon-neutral (CN) scenario, based on Coupled Model Intercomparison Project phase 6 model simulations. Here we propose a flexible heating policy (FHP), such that HL is determined strictly by temperature, and the associated air pollution benefit of shortening HL are examined by a global 3D chemical transport model GEOS-Chem. The study focused on the year 2019 with the current goal of elimination of severe PM2.5 pollution, and with the minimum HL estimated to provide up to a 24% reduction in severe PM2.5 pollution (daily mean PM2.5 > 150 μg m−3) over the NCP during periods of FHP implementation. For future CN policies, the NCP can achieve great air quality improvements by 2050, with more than 60% of days throughout the heating season with daily PM2.5 concentrations of <10 μg m−3, and 95% with <35 μg m−3. Although the SSP5-85 scenario may lead to reduced HLs, pollutant emissions are likely much higher than under CN scenarios, with pollution days of PM2.5> 100 μg m−3 still occurring frequently by 2050. Our results highlight that FHPs may effectively reduce severe PM2.5 pollution, and China’s carbon neutrality goals will play critical roles in mitigating air pollution and prolonged heating welfare during future heating season.

Impact of thermal structure of planetary boundary layer on aerosol pollution over urban regions in Northeast China

This study investigated the characteristics of aerosol pollution in three provincial capitals (Shenyang, Changchun, and Harbin) in Northeast China and the impact of the thermal structure of the planetary boundary layer (PBL) using surface air quality monitoring data and meteorological observations and sounding data from January 1 to January 20, 2020. The number of pollution days in Shenyang, Changchun, and Harbin were 13, 17, and 19, respectively, and the number of heavy pollution days was 4, 3, and 13, respectively. Harbin suffered the heaviest and longest pollution with the smallest diurnal variation between daytime low and nighttime high PM2.5. The atmosphere in Harbin was more stable than that in Shenyang and Changchun, and PM2.5 concentration in the three cities tended to increase with decreasing planetary boundary layer height (PBLH). The lower winter air temperature in Northeast China led to a shallower PBL and weaker ventilation coefficient, which in turn led to an increase in PM2.5 concentration, indicating that air temperature is the key meteorological factor affecting local pollution in Northeast China. The analysis of two typical pollution events showed that a warm advection aloft suppressed the development of the PBL in Shenyang. In contrast, the suppressed effect of warm advection on the PBL was weakened in Harbin, which originally had a low PBLH due to cold weather. Moreover, the daytime convective boundary layer in Harbin developed 1–2 h later than that in Shenyang; the delayed development of PBL during the daytime in Harbin was also conducive to poor air quality.

Application of stable index and transport index for regional air pollution over Twain-Hu Basin

Affected by stagnant and transmission air pollution, Regional pollution day (RPD) frequently occurs in Twain-Hu Basin. In the winter halfaear of 2015–2021 (November to March of following year), the Regional pollution days reached 331 days. A variety of weather systems together lead to regional air pollution. Based on the observation data of PM2.5 concentration and multi-source meteorological elements during the study period, the weather types of Regional pollution days in Twain-Hu Basin can be divided into four types by using the T-model (T-PCA) classification method, namely, uniform pressure field (42 days), front of cold high-pressure bottom (180 days), back of high-pressure (81 days), and low pressure with an inverted trough field (28 days). Under the influence of uniform pressure field and front of cold high-pressure bottom, it shows the meteorological characteristics of static pollution and transmission pollution, respectively. A stable index (STI) is constructed to describe the PM2.5 pollution caused by the stagnant weather, and a transport index (TRI) is constructed to describe the PM2.5 pollution caused by the transport weather. They have a satisfactory evaluation effect on PM2.5 pollution under the influence of uniform pressure field and front of cold high-pressure bottom, respectively. Interestingly, the correlation coefficients between the pollution index (A stable index + transport index) and PM2.5 concentration could increase obviously to 0.48–0.71 when A stable index and transport index are considered comprehensively. Furthermore, the validation in the winter halfaear of 2021/2022 show that the correlation coefficient of most stations is above 0.70. Therefore, satisfactory performance in validation suggests that this index construction method can be well applied to regional pollution assessment in Twain-Hu Basin.

Characteristics of Ozone Pollution and High-impact Meteorological Factors in Urban Cities: A Case of Suzhou

The problem of urban ozone (O3) pollution has become prominent in recent years. However, the meteorological factors associated with O3 pollution remain unclear. Analyzing the characteristics of O3 pollution in Suzhou, as a typical urban city, and exploring the high-impact meteorological factors with O3 pollution are crucial to the prevention and control of air pollution in this region. This study used correlation analysis and machine learning methods to analyze the variation in O3 concentration and the relationship between meteorological driving factors in Suzhou based on the O3 concentration data provided by Suzhou Environmental Monitoring Center and the contemporaneous meteorological observation data in Suzhou from April to September in 2015 to 2020. The results showed that: ① O3 pollution exceeding the standard rate was more than 20% in ozone seasons during the past six years; further, pollution days of O3 and the number of pollution days of O3 as the primary pollutant increased yearly. Evidently, the problem of O3 pollution has become increasingly prominent. ② The diurnal variations in O3 were unimodal with the valley point at 07:00 and the highest peak between 15:00 and 16:00. Similar trends were found in diurnal variations of both air temperature and solar radiation, but the daily highest peak came earlier than that of O3. The results also showed an apparent weekend effect of O3 concentration in 2017 and 2019 and a significant correlation between O3 concentration and solar irradiance during the week. In addition, the monthly variation in O3 concentration and pollution exceeding the standard rate was bimodal. ③The occurrence of ozone pollution was affected by various meteorological conditions. The maximum number of days appeared when daily sunshine hours lasted longer than 7 hours, with a daily maximum air temperature around 30℃, solar irradiance ranging from 350 to 440 kW·m-2, and relative humidity ranging from 50% to 75%, at which time the intensity of pollution was the strongest. When the wind speed of easterly wind was less than 1.5 m·s-1, or the wind speed of southwest wind was less than 3.5 m·s-1, moderate ozone pollution occurred. ④ An optimal prediction model of O3 concentration was established based on machine learning, which had good predictive ability for O3 concentration in April, May, July, and September but did not perform well when O3 concentration exceeded 200 μg·m-3. Meanwhile, it was found that solar radiation had the most obvious effect on O3 concentration, followed by relative humidity, whereas the temperature and wind were less important than the former two factors.

Distribution of Bacterial Concentration and Viability in Atmospheric Bioaerosols Under Different Weather Conditions in the Coastal Region of Qingdao

Bacteria are the most abundant microorganisms in atmospheric bioaerosols, widely distributed in the environment. Bioaerosol samples were collected using the FA-1 impact sampler from October 2013 to January 2021 in the coastal city of Qingdao, and samples stained with a BacLightTM bacterial viability kit were used to measure the concentrations of viable and non-viable bacteria with an epifluorescence microscope. The viable and non-viable bacteria in bioaerosols were characterized during different seasons, with particular attention paid to the distribution characteristics of bacteria on foggy, hazy, and dust days. The results showed that the mean concentrations of total bacteria were (1.06±0.68)×105 cells·m-3 in Qingdao during the sampling period, and those of viable and non-viable bacteria were (8.20±4.88)×103 cells·m-3and (9.74±6.72)×104 cells·m-3, respectively. The seasonal concentrations of non-viable bacteria were the highest in spring and winter and the lowest in summer, whereas that of viable bacteria was highest in spring, followed by those in summer and autumn, and the lowest in winter. Atmospheric bacterial concentrations fluctuated with by month, and total bacteria presented a similar variation pattern with that of non-viable bacteria. The monthly average concentration of non-viable bacteria showed the highest value in March during the spring and the lowest in June during the summer in 2021, whereas the highest value for viable bacteria occurred in May during the spring in 2021 and the lowest in December during the winter in 2020. Viable bacteria concentrations were significantly positively correlated with temperature and significantly negatively correlated with NO2, SO2, and CO. Non-viable bacteria were significantly positively correlated with PM. The bacteria in bioaerosol particles showed bimodal, unimodal, and skewed size distributions, varying with season and month. Under different weather conditions, the concentration of non-viable bacteria on dusty days was significantly higher than that on sunny, foggy, or hazy days, but the bacteria viability was as low as 6.85% due to long-distance transport. Anthropogenic pollution resulted in the lowest viability of bacteria at 4.10% on hazy days, whereas the highest viability in bacteria was 16.26% on foggy days due to high humidity. The size distribution of bacteria in bioaerosol particles under different pollution days showed a bimodal distribution, and the peak size depended on the weather type.

Growing pains for others: Using holidays to identify the pollution spillover between China and South Korea

Transboundary pollution spillovers have emerged as an important global issue in designing optimal regional economic policies. In particular, China and South Korea have been at odds over which country is the “source of evil” and responsible for their air pollution. This study investigates this issue and identifies the burden of the environmental externalities of pollution between China and South Korea. There are two novelties of this study: first, we employ a unique daily pollution indicator, that is, air visibility, to address data limitations. Second, we propose a novel identification strategy to examine the pollution spillovers of economic activities by exploiting the different holiday arrangements between China and South Korea. Evidence indicates significant bilateral environmental externalities between China and South Korea. Therefore, China and South Korea should make joint efforts to deal with their environmental challenges.

Metal based catalysts for hydrogen production reactions

Hydrogen is an outstanding source of energy and plays very important part in energy system. Hydrogen is one of the best energy carrier alternatives to fossil fuels because of its high energy density. It is very important to produce clean and renewable energy sources due to increasing population and pollution day by day. In 2018, the maximum hydrogen (94%) is manufactured from fossil fuels by steam reforming of natural gas, partial oxidation of the methane gas as well as coal gasification. The hydrogen production plays important role in any industrialized society, since hydrogen is required for many essential chemical processes. Several designed metal-based ideas can be employed as an efficient catalyst for hydrogen production for the alternate source of energy and society benefits. Proposed review is highlighting the different efficient strategies for hydrogen production.

Spatio-temporal Variation of Meteorological Influence on PM2.5 and PM10 over Major Urban Cities of Bangladesh

A detrended seasonal analysis on a 6-year (2013–2018) dataset of daily Particulate Matter (PM) concentration and meteorological parameters is performed to understand the spatio-temporal variation of PM and the seasonal influence of meteorological factors on PM pollution over 6 major urban cities of Bangladesh. Cross-correlation and multiple non-linear regression (MNLR) of air quality and meteorological data were used to explore the meteorology-PM interactions and their spatio-temporal variability. Meteorological influence on PM was found to be stronger in the southern part of the country relative to the northwestern part. MNLR analysis implied that meteorological parameters could explain up to 39% of daily PM variability during high pollution days. The deposition effect of relative humidity was prominent during the premonsoon season, while rainfall impact becomes dominant in the monsoon season, specifically in the northeastern region. Wind speed was observed to have a dilatory effect on PM variation, although wind seemed to carry sea aerosol in southern regions. In addition, the northwestern wind appeared to contribute to PM rise in most urban areas by carrying PM loading. In winter, the low temperature was found to favor PM accumulation, while in monsoon, high temperature causes PM rise, possibly by assisting atmospheric secondary aerosol formation. Solar radiation positively influenced atmospheric PM formation, and the influence was stronger in the northwestern region. It is shown that meteorological parameters influence the seasonal variability of PM, but the extent of this influence varies depending on temporal and regional factors.

Physical Activity, Air Pollution Exposure, and Lung Function Interactions Among Adults with COPD.

Although physical activity is strongly encouraged for patients with chronic obstructive pulmonary disease (COPD), it is unknown if physical activity affects daily exposure to air pollution, or whether it attenuates or exacerbates the effects of pollution on the airways among adults with COPD. Thirty former smokers with moderate-to-severe COPD in Boston were followed for 4 non-consecutive months in different seasons. We assessed daily lung function (forced expiratory volume in 1 second [FEV1] and forced vital capacity [FVC]), prior-day personal pollutant exposure measured by portable air quality monitors (fine particulate matter [PM2.5] nitrogen oxide [NO2], and ozone [O3]), and daily step count. We constructed multi-level linear mixed-effects models with random intercepts for person and person-observation month, adjusting for demographic/seasonal covariates to test if step count was associated with daily pollution exposure, and if associations between prior-day pollution and lung function differed based on prior-day step count. Where effect modification was found, we performed stratified analyses by tertile of step count. Higher daily step count was associated with higher same-day personal exposure to PM2.5, and O3 but not NO2. Each interquartile range (IQR) increment in step count was associated with 0.97 µg/m3 (95%CI: 0.30, 1.64) higher exposure to PM2.5 and 0.15 parts per billion (95% CI: -0.05, 0.35) higher exposure to O3 in adjusted models. We observed an interaction between prior-day NO2 and step count on FEV1 and FVC (Pinteraction<0.05) in which the negative associations between NO2 and lung function were reduced or absent at higher levels of daily activity. For example, FEV1 was 28.5mL (95%CI: -41.0, -15.9) lower per IQR of NO2 in the lowest tertile of step count, but there was no association in the highest tertile of step count (-1.6mL, 95% CI: -18.4, 15.2). Higher physical activity was associated with modestly higher daily exposure to PM2.5 and O3 and may attenuate the association between NO2 exposure and lung function.

Analysis of the PM2.5–O3 Pollution Characteristics and Its Potential Sources in Major Cities in the Central Plains Urban Agglomeration from 2014 to 2020

To highlight the characteristics of PM2.5–O3 pollution in the Central Plains Urban Agglomeration, spatial and temporal characteristics, key meteorological factors, and source pollution data for the area were analyzed. These data from the period 2014–2020 were obtained from state-controlled environmental monitoring stations in seven major cities of the agglomeration. The results revealed the following: (1) Spatially, the PM2.5–O3 pollution days were aggregated in the central area of Xinxiang and decreased toward the north and south. Temporally, during the 2014–2020 period, 50 days of PM2.5–O3 pollution were observed in the major cities of the Central Plains Urban Agglomeration, with an overall decreasing trend. (2) A low-temperature, high-pressure environment appeared unfavorable for the occurrence of PM2.5–O3 pollution days. Wind speeds of 2.14–2.19 m/s and a southerly direction increased the incidence of PM2.5–O3 pollution days. (3) The external transport range in summer was smaller and mainly originated from within Henan Province. These results can provide important reference information for achieving a synergistic control of PM2.5–O3 pollution, determining the meteorological causes, as well as the potential sources, of PM2.5–O3 pollution in polluted areas and promoting air pollution control.

Air pollution and anti-social behaviour: Evidence from a randomised lab-in-the-field experiment

We conducted a pre-registered randomised lab-in-the-field online experiment in Beijing, China, to explore the relationship between acute air pollution and anti-social behaviour. Our novel experimental design exploits naturally occurring discontinuities in pollution episodes to mimic an experimental setting in which pollution exposure is exogenously manipulated, thus allowing us to identify a causal relationship. Participants were randomly assigned to be surveyed on either high pollution or low pollution days, thereby exogenously varying the degree of pollution exposure. In addition, a subset of individuals surveyed on the high-pollution days received an additional ‘pollution alert’ to explore whether providing air pollution warnings influences (protective) behaviour. We used a set of well-established incentivised economic games to obtain clean measures of anti-social behaviour, as well as a range of secondary outcomes which may drive the proposed pollution-behaviour relationship. Our results indicate that exposure to acute air pollution had no statistically significant effect on anti-social behaviour, but significantly reduced both psychological and physiological well-being. However, these effects do not remain statistically significant after adjusting for multiple hypothesis testing. We find no evidence that pollution affects cognitive ability, present bias, discounting, or risk aversion, four potential pathways which may explain the relationship between pollution and anti-social behaviour. Our study adds to the growing calls for purposefully designed and pre-registered experiments that strengthen experimental (as opposed to correlational or quasi-experimental) identification and thus allow causal insights into the relationship between pollution and anti-social behaviour.

Characterisation of ambient air quality over two urban sites on the South African Highveld

Air pollution is an environmental-health challenge that many developing and developed countries are struggling to deal with. The purpose of our study was to characterise the ambient air quality during the year 2019–2020 over two urban sites of DiepKloof and Vanderbijilpark which are located on the South African Highveld. The study characterised PM10, PM2.5, SO2, NO2 and O3. Findings were that PM10, PM2.5, SO2 and NO2 ambient concentrations predominantly peaked during the winter season in June, July and August with mean concentrations of 48.6 µg/m3, 29.2 µg/m3, 38.6 µg/m3 and 12.6 µg/m3, respectively for the DiepKloof site while for the Vanderbijilpark site, winter mean for PM10, PM2.5 and SO2 were recorded at 124 µg/m3, 50.7 µg/m3 and 22.1 µg/m3, respectively. The average daily pollutant concentrations of the majority of pollutants were elevated above the WHO air quality guideline limits. Analysis of variance showed the seasonal variations had a significant (all p-values less than 0.01) effect on the variability of pollutant concentrations in both sites. The study attributes these elevated ambient pollutant levels to industrial, domestic and vehicular emission sources that are scattered over the South African Highveld. The study also highlighted the impact of the first lockdown period in South Africa indicating that the first three-week lockdown had a significant (p-values less than 0.001) impact on the variability of pollutant concentrations in both Diep Kloof and Vanderbijlpark. The study also established that pollutant concentrations were more significantly affected by wind direction in the more industrialized Vanderbijlpark than in Diep Kloof. The study contributes towards air quality monitoring and management policy formulation both in South Africa and other African countries. Furthermore, the study contributes towards the academic body of knowledge. To curtail pollutant emissions governments have several options including tightening the air quality regulatory frameworks as well as establishing and supporting community-based air quality advocates. Air quality advocates can act as a conduit in raising general public awareness regarding the impact of air pollution on human health.

Influence of extratropical cyclones on air quality in Beijing

Extratropical cyclones (ETCs) are one of the primary weather systems affecting China. However, atmospheric environmental effects generated under the control of ETCs are rarely reported. In this study, we investigate air quality in Beijing from the perspective of ETCs. The ETCs affecting Beijing from 2014 to 2021 are tracked using the 850 hPa relative vorticity cyclone tracking algorithm. We classify the identified ETCs by cyclogenesis region, which includes 228 northern cyclones (NCs) and 41 southern cyclones (SCs). Generally, NCs are more likely to cause air pollution. For 27.4% and 16.3% of the days under the control of NCs, PM2.5 and PM10 pollution occur, respectively. These are mainly associated with high northwest wind and enhanced sinking motion. SCs are conducive to good or moderate air quality. The PM2.5/PM10 pollution days account for 20.0%/5.0% of total days under the control of SCs, mainly due to enhanced rising motion and increased precipitation. Nevertheless, the influence of NCs/SCs on air quality shows significant seasonal differences. NCs negatively impact air quality in most seasons, except in summer. SCs tend to reduce the probability of air pollution in summer and autumn. Higher chances of air pollution associated with SCs occur in spring and winter. For a typical NC case that causes a dust storm, dust backflow occurs after the NC moves away, resulting in secondary pollution. A typical SC case generates different atmospheric environmental effects owing to the changes in its location. These results highlight the importance of ETCs for air quality in Beijing.

Correlation between surface PM2.5 and O3 in eastern China during 2015–2019: Spatiotemporal variations and meteorological impacts

PM2.5 and ozone (O3) are two major air pollutants in China. A systematic evaluation of the spatiotemporal variations in the correlation between them is essential for their coordinated prevention and control. In this study, we investigated the spatiotemporal variations in the correlations between the surface PM2.5 and O3 concentrations, and the influences of the meteorological parameters in eastern China were analyzed. The major findings of this study are as follows. From 2015 to 2019, the annual number of PM2.5 (O3) pollution days in eastern China decreased (increased) by 8.6% (19.2%). In the three developed regions, the O3 concentrations increased with increasing PM2.5 when the PM2.5 concentrations were less than ∼50 μg m−3; while the O3 concentrations decreased with increasing PM2.5 when the PM2.5 concentrations were greater than ∼50 μg m−3, except in the Pearl River Delta. The daily average PM2.5 concentrations were positively correlated with the O3 concentrations in most regions and seasons in eastern China, but they were negatively correlated with the O3 concentrations in the cold season, especially in the NCP. The correlation between these two pollutants exhibited notable north-south and seasonal variations, and it tended to be more positively correlated as the PM2.5 concentration decreased. Further investigation revealed that the temperature was positively correlated with the O3 concentration, while they exhibited different seasonal variations with the PM2.5 concentration. The relative humidity was negatively correlated with the O3 concentration and positively correlated with the PM2.5 concentration in the NCP, but was negatively correlated with it in the YRD and PRD. The temperature was a significant meteorological parameter influencing the correlation between the PM2.5 and O3 concentrations, with a coefficient of determination (R2) of 0.83. Under high-temperature conditions, the PM2.5 and O3 concentrations exhibited a stronger positive correlation. These results provide guidance for coordinating PM2.5 and O3 pollution prevention and control in eastern China.