Trends Of PM2 Research Articles

Long-term (2003–2018) trends in aerosol chemical components at a high-altitude background station in the western North Pacific: Impact of long-range transport from continental Asia

This study examined the long-term trends in chemical components in PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) samples collected at Lulin Atmospheric Background Station (LABS) located on the summit of Mt. Lulin (2862 m above mean sea level) in Taiwan in the western North Pacific during 2003–2018. High ambient concentrations of PM2.5 and its chemical components were observed during March and April every year. This enhancement was primarily associated with the long-range transport of biomass burning (BB) smoke emissions from Indochina, as revealed from cluster analysis of backward air mass trajectories. The decreasing trends in ambient concentrations of organic carbon (−0.67% yr−1; p = 0.01), elemental carbon (−0.48% yr−1; p = 0.18), and non–sea-salt (nss) K+ (−0.71% yr−1; p = 0.04) during 2003–2018 indicated a declining effect of transported BB aerosol over the western North Pacific. These findings were supported by the decreasing trend in levoglucosan (−0.26% yr−1; p = 0.20) during the period affected by the long-range transport of BB aerosol. However, NO3− displayed an increasing trend (0.71% yr−1; p = 0.003) with considerable enhancement resulting from the air masses transported from the Asian continent. Given that the decreasing trends were for the majority of the chemical components, the columnar aerosol optical depth (AOD) also demonstrated a decreasing trend (−1.04% yr−1; p = 0.0001) during 2006–2018. Overall decreasing trends in ambient (carbonaceous aerosol and nss-K+) as well as columnar (e.g., AOD) aerosol loadings at the LABS may influence the regional climate, which warrants further investigations. This study provides an improved understanding of the long-term trends in PM2.5 chemical components over the western North Pacific, and the results would be highly useful in model simulations for evaluating the effects of BB transport on an area.

Air pollution trend in Chandigarh city situated in Indo-Gangetic Plains: Understanding seasonality and impact of mitigation strategies

The long-term trend of air pollutants was studied in Chandigarh, located in Indo-Gangetic Plains of India. The SPM, PM10, NOx, and SO2 depict site-specific variation having different anthropogenic activities. The results indicate that PM10 levels in Chandigarh remain higher than the prescribed annual ambient air quality standards (60 μg m−3) of India. Seasonal Kendall test indicates a declining trend of PM10 for the year 2003 to 2018 at an industrial and commercial site (1996–2016). There is a significant increase in NOx levels at all locations except at commercial sites. The results of the linear regression model and Theil–Sen slope show that SPM is declining at all locations, but results are not statistically significant. Interestingly, PM10 levels at the industrial site display a significant declining trend (1.3% year−1). Similarly, NOx levels are increasing at all sites but having a statistically significant trend at a rural location (8.9% year−1) and residential site (15.2% year−1). Air pollutants show strong seasonal variability having a higher concentration in post-monsoon and winter season, which found to be linked with regional anthropogenic activities such as crop residue burning and use of solid biomass fuel for cooking and other purposes. Lowest PM10 levels were observed during the monsoon and having a decline of 47.4–66.4% as compared to winter levels. Site-specific variations in air pollutants were found to be associated with air quality improvement policies such as shifting of an interstate bus terminal, ban on diesel autos, including strict implementation of air quality norms on industries. As the relative contribution of various pollution sources is still unknown, the seasonal pattern of pollutants will help in knowing the background concentration of pollutants and could help to formulate evidence-based policies to mitigate air pollution under National Clean Air Programme (NCAP).

Characterization, sources and risk assessment of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) and nitrated PAHs (NPAHs) in Harbin, a cold city in Northern China

Inhalation of atmospheric particulates is an significant way for polycyclic aromatic hydrocarbons (PAHs) and substituted PAHs (SPAHs) to enter the human lungs. Some SPAHs are more virulent than parent PAHs. Atmospheric fine particulate matter (PM2.5) samples were obtained at Harbin Institute of Technology (HIT) in Harbin, China. This study provided the first description, source apportionment, and health risk for PM2.5-bound 16 PAHs and 16 nitrated PAHs (NPAHs) in cold regions of China. On average, the PM2.5, PM2.5-bound PAHs and NPAHs concentrations were 80.8 μg/m3, 86.9 ng/m³ and 5.48 ng/m³. Significant increases in PM2.5 (274 μg/m³) and PM2.5-bound NPAHs (24.7 ng/m³) concentrations were measured during the straw burning in autumn, while the concentration of PM2.5-bound PAHs (215 ng/m³) increased obviously in winter. Source apportionment showed that the main source of PAHs was combustion, while besides direct emissions, about 20% of NPAHs came from the secondary formation. Controlling coal combustion and biomass burning might be an effective measure to improve air quality during the heating period in Harbin. The influence of meteorological conditions on PAHs and NPAHs concentration indicated that pollutants were more susceptible to meteorological conditions during the heating period than during the non-heating period, especially for PAHs. The health risk analysis indicated that the highest health risk caused by exposure to the PM2.5-bound PAHs and NPAHs was in winter, and this was inconsistent with the trend of PM2.5 pollution. Cancer risk assessments demonstrated the potential cancer risk at this PAHs and NPAHs concentration level.

Long-term trends in PM2.5 mass and particle number concentrations in urban air: The impacts of mitigation measures and extreme events due to changing climates

Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM2.5) and particle number concentrations (PNC), and the factors that influenced the trends. Mann-Kendall test, Sen’s slope estimator, the generalised additive model, seasonal decomposition of time series by LOESS (locally estimated scatterplot smoothing) and the Buishand range test were applied. Both PM2.5 and PNC showed significant negative monotonic trends (0.03–0.6 μg m−3. yr−1 and 0.40–3.8 × 103 particles. cm−3. yr−1, respectively) except Brisbane (+0.1 μg m−3. yr−1 and +53 particles. cm−3. yr−1, respectively). For the period covered in this study, temperature increased (0.03–0.07 °C.yr−1) in all cities except London; precipitation decreased (0.02–1.4 mm. yr−1) except in Helsinki; and wind speed was reduced in Brisbane and Rochester but increased in Helsinki, London and Augsburg. At the change-points, temperature increase in cold cities influenced PNC while shifts in precipitation and wind speed affected PM2.5. Based on the LOESS trend, extreme events such as dust storms and wildfires resulting from changing climates caused a positive step-change in concentrations, particularly for PM2.5. In contrast, among the mitigation measures, controlling sulphur in fuels caused a negative step-change, especially for PNC. Policies regarding traffic and fleet management (e.g. low emission zones) that were implemented only in certain areas or in a progressive uptake (e.g. Euro emission standards), resulted to gradual reductions in concentrations. Therefore, as this study has clearly shown that PM2.5 and PNC were influenced differently by the impacts of the changing climate and by the mitigation measures, both metrics must be considered in urban air quality management.

2009–2017 trends of PM10 in the legendary Riotinto mining district of SW Spain

Abstract This study is the first to perform a chemical characterization and source contribution of particulate matter (PM10) occurring through the abandonment and reopening of a historical sulphide mine. This long-range analysis covers the period 2009–2017 in the Riotinto mining district (Iberian Pyrite Belt, Southwestern Spain), which is a mining district of world-class importance. This mine represents a susceptible anthropogenic emission source of toxic sulphide-associated elements in atmospheric particulate matter, which affects the air quality of the nearby areas. A total of 567 samples of 24 h were collected from 2009 to 2017 in a rural station. The filters were analysed to determine Organic and elemental carbon, mayor and trace elements, and water soluble compounds of PM10. The trends of PM10 and geochemical characterization were studied considering the following periods: mine abandonment (2009–2014) and the mine's state during (2015–2016) and after (2017) implementation of new emission abatement technology at this mine. The results revealed relatively high concentrations of Cu, Zn, Pb, As, Sb, and Bi during 2015–2016. A reduction of 42–59% was observed after 2017 for the same elements in PM10. Five sources were identified: regional, mining, aged sea salt, combustion + traffic and crustal, using positive matrix factorization model (PMF5). The contribution of the mining factor was higher in the reopening period (4.2 μg m−3, 16%). These results have been confirmed by As speciation analysis, in which the low extraction percentage obtained is related to the origin of the metalloids associated with sulphide ores. The reduction of emissions of atmospheric particulate matter in the mining processes is the main objective in the implementation of measures considering the technological progress for cleaner and sustainable mining. In the case of reopening of historical mines, with low ore grade and greater extraction of ore and rock, a major effort must be made in order to avoid a negative influence on the environment and human health.

Malaysian Traffic Police in Highly Populated Areas: Is it Safe Working Outdoors on a Daily Basis?

ABSTRACT Previous studies have reported on the increment in the concentration levels of outdoor air pollution affecting the lung functions among traffic police as they work outdoors, on an average, for 12 hours daily. This paper provides an analysis of the outdoor air pollutant trends. It is novel in considering how it can be used to understand the impact on the 1,149 Malaysian Traffic Police in the states of Kuala Lumpur (KL) and Johor Bahru (JB). The study used 165, 604 data from a nine-year database (2009–2017) of selected Malaysian air monitoring stations in KL and JB. The statistical analysis showed that the yearly trends of PM10 were above the Malaysian Ambient Air Quality Guideline (MAAQG) standard while the SO2, O3, NO2, and CO readings were below the standard. An increasing trend was noticed in the total number of vehicles in both states from 2009 to 2017. All the pollutants were positively correlated with each other, indicating that most of the pollutants are from similar sources. There is a strong positive correlation between the total number of vehicles and CO, NO2, and O3. This study proves the trends and consequences of outdoor air pollutants coupled with the rise in the number of vehicles that can affect respiratory health and well-being of the traffic police personnel. As a resolution to this, an efficient risk control such as air monitoring system for traffic police is necessary. The findings of this study will facilitate its usefulness to the authorities, management, policymakers, and researchers in the years ahead.

Changes in Air Quality during the COVID-19 Lockdown in Singapore and Associations with Human Mobility Trends

On the 7th of April, the Singaporean government enforced strict lockdown measures with the aim of reducing the transmission chain of the coronavirus disease 2019. This had a significant impact on the movement of people within the country. Our study aims to quantify the impact that these measures had on outdoor air pollution levels. We obtained air quality and weather data from April 2016 to May 2020, satellite data for 2019 and 2020 and mobility data for 2020 from Apple, Google, and the Singaporean Housing & Development Board. We determined that outdoor air pollution during the lockdown significantly decreased when compared with the same period in the previous four years even if we included corrections for long time trends in the analysis. The concentrations of the following pollutants PM10, PM2.5, NO2, CO, and SO2 decreased by 23, 29, 54, 6, and 52%, respectively, whilst that of O3 increased by 18%. The Pollutant Standard Index decreased by 19%. The trends of PM2.5 and NO2 were significantly correlated with mobility data. The NO2 and SO2 tropospheric concentrations and the total aerosol optical depth at 550 nm obtained from satellite data during the lockdown in 2020 were also lower than during the same period in 2019. Our results can be used to evaluate possible mitigation strategies for outdoor air quality in a longer term beyond this lockdown.

Variation Characteristics of Mass Concentration of Inhalable Particles in Qingdao, China

The geographical condition of Qingdao, China is relatively special; the transport of various inland pollutants, the emissions of marine aerosol and local pollutants will have an impact on the changes of atmospheric aerosol concentration. By using the stability classification method, trajectory clustering analysis and the NOAA HYSPLIT model, the seasonal distribution characteristics of atmospheric inhalable particulate matter concentration in Qingdao, China and its relationship with meteorological conditions, mixed layer height, and the seasonal characteristics of Qingdao pollutant transport were analyzed. The results show that the variation trends of PM2.5 and PM10 were about the same, and there are obvious seasonal differences, which are high in winter and spring, and low in summer and autumn. The concentration of inhalable particulate matter has a negative correlation with temperature, wind speed and relative humidity. The concentration of inhalable particulate matter is distinct in different relative humidity ranges. When the wind speed is less than 3 - 4 m/s, there are more inhalable particles, while the mass concentration shows obvious reduction with the wind speed more than 4 m/s. There is a significant negative correlation between the mass concentration of pollutants and the daily maximum mixed layer height. The larger the concentration of pollutants, the smaller the thickness of the daily largest mixed layer. Conversely, the smaller the mass concentration of pollutants, the larger the thickness of the daily largest mixed layer. The pollutant transport in Qingdao has obvious seasonal characteristics. The air mass in spring, autumn and winter is mainly medium-long distance transport from Mongolia and southern Russia, and medium-short distance transport from Inner Mongolia and northeast of China. The source of air masses in summer is mainly transported from the eastern and sea areas.

Evaluating the effects of surface O3 on three main food crops across China during 2015–2018

In order to tackle China’s severe air pollution issue, the government has released the “Air Pollution Prevention and Control Action Plan” (known simply as the “Action Plan”) since 2013. A recent study reported a decreased trend in PM2.5 concentrations over 2013–2017, but O3 pollution has become more serious. However, the effects of surface O3 on crops are unclear after the implementation of the “Action Plan”. Here, we evaluated the potential negative effects of surface O3 on three main food crops (winter wheat, maize and rice) across China during 2015–2018 using nationwide O3 monitoring data and AOT40-yield response functions. Results suggested that mean O3 concentration, AOT40 and relative yield loss in China showed an overall upward trend from 2015 to 2018. During winter wheat, maize, single rice, double-early rice, and double-late rice growing seasons, mean O3 concentration in recent years ranged from 38.6 to 46.9 ppb, 40.2–43.9 ppb, 39.3–42.2 ppb, 33.8–40.0 ppb, and 35.9–39.1 ppb, respectively, and AOT40 mean values ranged from 8.5 to 14.3 ppm h, 10.5–13.4 ppm h, 9.8–11.9 ppm h, 5.2–9.2 ppm h, and 8.0–9.5 ppm h, respectively. O3-induced yield reductions were estimated to range from 20.1 to 33.3% for winter wheat, 5.0–6.3% for maize, 7.3–8.8% for single rice, 3.9–6.8% for double-early rice and 5.9–7.1% for double-late rice. O3-induced production losses for winter wheat, maize, single rice, double-early rice, and double-late rice totaled 39.5–88.2 million metric tons, 12.6–21.0 million metric tons, 9.5–11.3 million metric tons, 1.2–1.8 million metric tons, and 2.2–2.7 million metric tons, respectively, and the corresponding economic losses totaled 14.3–32.0 billion US$, 3.9–6.5 billion US$, 3.9–4.6 billion US$, 0.5–0.7 billion US$, and 0.9–1.1 billion US$, respectively. Our results suggested that the government should take effective measures to reduce O3 pollution and its effects on agricultural production.

PM2.5 Analysis and Prediction Based on Seasonal Time Series Model

The PM2.5 data in Hefei area from 2014 to 2018 were collected through the website of meteorological bureau, and the data were analyzed and modeled with the help of statistical analysis software SPSS and EVIEWS. Firstly, the annual and seasonal distribution characteristics and trend of PM2.5 data in Hefei area during the past five years were analyzed. It was concluded that the distribution of PM2.5 had periodic characteristics, and the air quality in summer was the best and that in winter was the worst. According to the results of statistical analysis, PM2.5 data had seasonal characteristics. On this basis, the Holt-Winters additive model and SARIMA model in seasonal time series model were selected to model and predict. The prediction values of the two models were compared with the real values. The results showed that the prediction accuracy of the Holt-Winters additive model was slightly higher than that of the SARIMA model.

Study on the applicability of key parameters from dust emission scheme in WRF/Chem over northwestern China

In order to more accurate quantitative simulation and forecast of sandstorm in northwest China, in this paper, the dust process occurred in northwest China was simulated by using the WRF/Chem model coupling of Shao2004 dust emission parameterization scheme. The influence of key parameter C in Shao2004 scheme is analyzed set at different values on simulated spatial and temporal dust concentration, estimated vertical dust flux and estimated PM10 and PM2.5 concentration of six stations in northwest China. And by comparing the concentration of PM concentration observed at the sites, the results were listed as: Parameter C has an significant influence on the simulation dust scope and maximum center value of dust concentration and vertical dust flux; Different C values can well simulate the variation trend of PM10 and PM2.5 concentration in dust weather, but only when the C value set as 1, this model can more accurately simulate the change of PM10 and PM2.5 concentration in the dust process in northwest China.

Air Quality Trend of PM10. Statistical Models for Assessing the Air Quality Impact of Environmental Policies

A statistical modelling of PM10 concentration (2006–2015) is applied to understand the behaviour, to know the influence of the variables to exposure risk, to treat the missing data to evaluate air quality, and to estimate data for those sites where they are not available. The study area, Castellón region (Spain), is a strategic area in the framework of EU pollution control. A decrease of PM10 is observed for industrial and urban stations. In the case of rural stations, the levels remain constant throughout the study period. The contribution of anthropogenic sources has been estimated through the PM10 background of the study area. The behaviour of PM10 annual trend is tri-modal for industrial and urban stations and bi-modal in the case of rural stations. The EU Normative suggests that 90% of the data per year are necessary to control air quality. Thus, interpolation statistical methods are presented to fill missing data: Linear Interpolation, Exponential Interpolation, and Kalman Smoothing. This study also focuses on testing the goodness of these methods in order to find the ones that better approach the gaps. After analyzing graphically and using the RMSE the last method is confirmed to be the best option.

Trends in PM2.5 transition metals in urban areas across the United States

Using data from the Environmental Protection Agency’s Chemical Speciation Network, we have characterized trends in PM2.5 transition metals in urban areas across the United States for the period 2001–2016. The metals included in this analysis—Cr, Cu, Fe, Mn, Ni, V, and Zn—were selected based upon their abundance in PM2.5, known sources, and links to toxicity. Ten cities were included to provide broad geographic coverage, diverse source influences, and climatology: Atlanta (ATL), Baltimore (BAL), Chicago (CHI), Dallas (DAL), Denver (DEN), Los Angeles (LA), New York City (NYC), Phoenix (PHX), Seattle (SEA), and St. Louis (STL). The concentrations of V and Zn decreased in all ten cities, though the V decreases were more substantial. Cr concentrations increased in cities in the East and Midwest, with a pronounced spike in concentrations in 2013. The National Emissions Inventory was used to link sources with the observed trends; however, the causes of the broad Cr concentration increases and 2013 spike are not clear. Analysis of PM2.5 metal concentrations in port versus non-port cities showed different trends for Ni, suggesting an important but decreasing influence of marine emissions. The concentrations of most PM2.5 metals decreased in LA, STL, BAL, and SEA while concentrations of four of the seven metals (Cr, Fe, Mn, Ni) increased in DAL over the same time. Comparisons of the individual metals to overall trends in PM2.5 suggest decoupled sources and processes affecting each. These metals may have an enhanced toxicity compared to other chemical species present in PM, so the results have implications for strategies to measure exposures to PM and the resulting human health effects.

Changes in the PM2.5 concentration from 2015 to 2017 in Bijie City, Guizhou Province, China

Atmospheric environmental problems have received more and more attention. Research of PM2.5 has become the core issue of atmospheric environment research. This paper takes the PM2.5 data of the Bijie City from 2015 to 2017 as the research object, and investigates the trend in PM2.5 concentration. The PM2.5 concentration generally showed a decline trend, and the air quality was relatively good. The PM2.5 concentration in Bijie City was basically maintained within the secondary concentration limit of the air environmental quality. The PM2.5 concentration in Bijie City has a weekend effect, and the concentrations on the weekends were slightly higher than those on weekdays. This study can provide a scientific basis for the prevention and control of air pollutants in the Bijie City.

Short-term PM2.5 forecasting based on CEEMD-RF in five cities of China.

The development of industrial civilization has greatly enriched the material and spiritual life of human beings, but it is accompanied by the intensification of the consumption of earth resources and environmental pollution. The smog that has emerged in various parts of China in recent years is a typical problem, which not only endangers human health but also affects normal human work and life. It is difficult to control smog in a short time productively, so people need to understand the rule of smog formation gradually, and effectively predict the PM2.5 index to help people continuously analyze relevant mechanisms and timely protect-related hazards. This paper proposes a hybrid model that uses the Complementary Ensemble Empirical Modal Decomposition algorithm to mine the information in the original PM2.5 sequence and then predicts the pertinent random forests. The trend of PM2.5 concentration during the decomposition process is effectively reflected, and the decomposition sequence is modeled by the high tolerance of the random forest to the noise data and the good fitting ability. In the modeling process, the parameters are optimized according to the evaluation function of the model on the verification set, and eventually, the prediction sequences are superimposed to obtain the final predicted PM2.5 concentration value. The validity of the model is verified by the data of several Chinese cities with different geographical features in the past 5years. The results show that the recommendation model is higher than other comparison models in terms of model stability and prediction accuracy.

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Assessment of Ambient Air Pollution in Langkawi Island, Malaysia

For many years, Southeast Asia region encountered several ongoing air pollution episodes. These episodes had indirectly significant impact on the air quality of neighboring countries. Hence, this study aims to assess the characteristics and trend of air pollution in Malaysia particularly at Langkawi Island. Air pollution hourly monitoring records from 2003 to 2017 were used in analyzing the statistical data analysis. Eight parameters were selected in this study which known as PM10, CO, SO2, NO2, O3, relative humidity (RH), temperature (T) and wind speed (WS). The results showed that the hourly trends of PM10, CO, SO2, NO2 and O3 in Langkawi Island were below the MAAQG standard. The results also indicated that dispersion of PM10 in Malaysia were significantly affected by temperature, wind speed and relative humidity.

Trend analysis of observational PM10 concentrations in Shimla city, India

The present study aims to evaluate the long-term trends of PM10 at two monitoring stations (an urban and a background station) in Shimla city, in India during the period 2011–2017. The highest daily mean concentrations were determined to be 176 μg/m3 and 152 μg/m3 respectively at the urban and the background monitoring locations. Similarly, the annual mean concentrations at the monitoring locations were determined to be 59 μg/m3 and 45 μg/m3 respectively for urban and background concentrations. Exceedance factors determined showed that at the urban monitoring location the ranges varied between ‘moderate to high’ while at the background monitoring station it remained at ‘moderate’ levels. Seasonal analysis study carried out revealed that higher concentrations were observed during summer in comparison to winter with the least concentrations occurring during the monsoon season. A regression analysis was carried out to test the interdependency of the PM10 with other pollutants and a positive correlation was observed between PM10 and NO2 and SO2. Similarly, correlation of PM10 with meteorological parameters such as wind speed and temperature were found to be positive while for parameters like precipitation and relative humidity it was negative. The paper also presents a critical discussion on the outcomes of the trend analysis study. This includes design and location of additional monitoring sites to adequately represent the actual ambient air quality conditions in Himachal Pradesh.

Recent spatial gradients and time trends in Dhaka, Bangladesh, air pollution and their human health implications

ABSTRACTDhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM2.5 (<2.5 µm in aerodynamic diameter), PM10 (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO2, NO2, CO, and O3) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM2.5 and PM10 being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM2.5 and PM10) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM2.5 (72% of total study days), followed by PM10 (40% of total study days), O3 (1.7% of total study days), SO2 (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO2 (5.6 ppb yr−1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr−1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM2.5 (−4.6 µg/m3 yr−1, 95% CI: −12.7, 3.6) and PM10 (−2.7 µg/m3 yr−1, 95% CI: −7.9, 2.5) were observed during this study period, the PM2.5 concentration is still too high (~ 82.0 µg/m3) and can cause severe impact on human health.Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.

A tale of two cities: is air pollution improving in Paris and London?

Paris and London are Europe's two megacities and both experience poor air quality with systemic breaches of the NO2 limit value. Policy initiatives have been taken to address this: some European-wide (e.g. Euro emission standards); others local (e.g. Low Emission Zone, LEZ). Trends in NOX, NO2 and particulate matter (PM10, PM2.5) for 2005–2016 in background and roadside locations; and trends in traffic increments were calculated in both cities to address their impact. Trends in traffic counts and the distribution in Euro standards for diesel vehicles were also evaluated. Linear-mixed effect models were built to determine the main determinants of traffic concentrations. There was an overall increase in roadside NO2 in 2005–2009 in both cities followed by a decrease of ∼5% year−1 from 2010. Downward trends were associated with the introduction of Euro V heavy vehicles. Despite NO2 decreasing, at current rates, roads will need 20 (Paris) and 193 years (London) to achieve the European Limit Value (40 μg m−3 annual mean). Euro 5 light diesel vehicles were associated with the decrease in roadside PM10. An increase in motorcycles in London since 2010 contributed to the lack of significant trend in PM2.5 roadside increment in 2010–16.