In this study, we analysed a data set from 10 low-cost PM₂.₅ sensors using the Internet of Things (IoT) for air quality monitoring in Mae Sot, which is one of the most vulnerable areas for high PM₂.₅ concentration in Thailand, during the 2018 burning season. Our objectives were to understand the nature of the plume movement and to investigate possibilities of adopting IoT sensors for near real-time forecasting of PM₂.₅ concentrations. Sensor data including PM₂.₅ and meteorological parameters (wind speed and direction) were collected online every 2 min where data were grouped into four zones and averaged every 15 min interval. Results of diurnal profile plot revealed that PM₂.₅ concentrations were high around early to late morning (3:00–9:00) and gradually reduced till the rest of the day. During the biomass burning period, maximum daily average concentration recorded by the sensors was 280 μg/m³ at Thai Samakkhi while the minimum was 13 μg/m³ at Mae Sot. Lag time concentrations, attributed by biomass burning (hotspots), significantly influenced the formation of PM₂.₅ while the disappearance of PM₂.₅ was found to be influenced by moderate wind speed. The PM₂.₅ concentrations of the next 15 min at the downwind zone (MG) were predicted using lag time concentrations with different wind categories. The next 15 min predictions of PM₂.₅ at MG were found to be mainly influenced by its lag time concentrations (MG_Lag); with higher wind speed, however, the lag time concentrations from the upwind zones (MS_Lag and TS_Lag) started to show more influence. From this study, we have found that low-cost IoT sensors provide not only real-time monitoring information but also demonstrate great potential as an effective tool to understand the PM₂.₅ plume movement with temporal variation and geo-specific location.

Africa's economy is growing faster than any other continent and it has been estimated that the middle class in Africa now exceeds 350 million people. This has meant a parallel increase in the importation of consumer goods and in the implementation of communication and information technologies (ICT), but also in the generation of large quantities of e-waste. However, inadequate infrastructure development remains a major constraint to the continent's economic growth and these highly toxic residues are not always adequately managed. Few studies have been conducted to date assessing the possible association between socioeconomic development factors, including e-waste generation, and blood levels of inorganic elements in African population. To disclose the role of geographical, anthropogenic, and socioeconomic development determinants on the blood levels of Ag, Al, As, Be, Cd, Co, Cr, Hg, Ni, Pb, Sb, and V —all of them frequently found in e-waste—, an immigrant population-based study was made including a total of 245 subjects from 16 countries recently arrived to the Canary Islands (Spain). Women presented higher levels of blood elements than men, and Northern Africans (Moroccans) were the most contaminated. People from low-income countries exhibited significantly lower blood levels of inorganic elements than those from middle-income countries. We found a significant association between the use of motor vehicles and the implementation of information and communication technologies (ICT) and the level of contamination. Immigrants from the countries with a high volume of imports of second-hand electronic equipment, telephone and internet use had higher levels of inorganic elements. In general terms, the higher level of economic development the higher the blood levels of inorganic pollutants, suggesting that the economic development of Africa, in parallel to e-waste generation and the existence of informal recycling sites, have directly affected the level of contamination of the population of the continent.

Multiple systematic reviews and meta-analyses linked prenatal exposure to ambient air pollutants to adverse birth outcomes with mixed findings, including results indicating positive, negative, and null associations across the pregnancy periods. The objective of this study was to systematically summarise systematic reviews and meta-analyses on air pollutants and birth outcomes to assess the overall epidemiological evidence. Systematic reviews with/without meta-analyses on the association between air pollutants (NO₂, CO, O₃, SO₂, PM₂.₅, and PM₁₀) and birth outcomes (preterm birth; stillbirth; spontaneous abortion; birth weight; low birth weight, LBW; small-for-gestational-age) up to March 30, 2022 were included. We searched PubMed, CINAHL, Scopus, Medline, Embase, and the Web of Science Core Collection, systematic reviews repositories, grey literature databases, internet search engines, and references of included studies. The consistency in the directions of the effect estimates was classified as more consistent positive or negative, less consistent positive or negative, unclear, and consistently null. Next, the confidence in the direction was rated as either convincing, probable, limited-suggestive, or limited non-conclusive evidence. Final synthesis included 36 systematic reviews (21 with and 15 without meta-analyses) that contained 295 distinct primary studies. PM₂.₅ showed more consistent positive associations than other pollutants. The positive exposure-outcome associations based on the entire pregnancy period were more consistent than trimester-specific exposure averages. For whole pregnancy exposure, a more consistent positive association was found for PM₂.₅ and birth weight reductions, particulate matter and spontaneous abortion, and SO₂ and LBW. Other exposure-outcome associations mostly showed less consistent positive associations and few unclear directions of associations. Almost all associations showed probable evidence. The available evidence indicates plausible causal effects of criteria air pollutants on birth outcomes. To strengthen the evidence, more high-quality studies are required, particularly from understudied settings, such as low-and-middle-income countries. However, the current evidence may warrant the adoption of the precautionary principle.

This systematic review and meta-analysis was performed to obtain updated evidence regarding the short-term effect of ozone on respiratory mortality in China. We systematically searched the Embase, PubMed, Scopus, Web of Science, China National Knowledge Internet, and Wanfang databases for relevant studies. After screening based on the inclusion criteria, 12 studies with 19 estimates were selected for further meta-analysis. The results revealed that respiratory mortality significantly increased by 0.55% (95% confidence interval: 0.24%–0.85%; Q = 39.47, I² = 54.4%, P = 0.002, tau² < 10⁻⁵) for every 10-μg/m³ increase in the maximum 8-h average concentration of ozone. Furthermore, differences in combined estimates were observed between various regions and lag structures. The combined effect of single-day lags was generally larger than that of multiday lags; the estimate of mortality for the population in the north was larger than that for the population in the south. The sensitivity analysis demonstrated that the main findings were stable; funnel plots with Egger’s and Begg’s tests indicated no significant publication bias in our analysis.

A winter air pollution episode was observed in Hangzhou, South China, during the Second World Internet Conference, 2015. To study the pollution characteristics and underlying causes, the Weather Research and Forecasting with Chemistry model was used to simulate the spatial and temporal evolution of the pollution episode from December 8 to 19, 2015. In addition to scenario simulations, analysis of the atmospheric trajectory and synoptic weather conditions were also performed. The results demonstrated that control measures implemented during the week preceding the conference reduced the fine particulate matter (PM2.5) pollution level to some extent, with a decline in the total PM2.5 concentration in Hangzhou of 15% (7%–25% daily). Pollutant long-range transport, which occurred due to a southward intrusion of strong cold air driven by the Siberia High, led to severe pollution in Hangzhou on December 15, 2015, accounting for 85% of the PM2.5 concentration. This study provides new insights into the challenge of winter pollution prevention in Hangzhou. For adequate pollution prevention, more regional collaborations should be fostered when creating policies for northern China.

In urbanized regions with expansive impervious surfaces and often low vegetation cover, air pollution due to motor vehicles and other combustion sources, is a problem. The poor air quality days in Montreal, Quebec are mainly due to fine particulate matter and ozone. Businesses using wood ovens are a source of particulates. Careful vegetation selection and increased green roof usage can improve air quality. This paper reviews different green roofs and the capability of plants in particulate matter (PM), ozone (O3) as well as nitrogen dioxide (NO2) level reductions. Both the recommended green roof category and plants to reduce these pollutants in Montreal's zone 5 hardiness region are provided. Green roofs with larger vegetation including shrubs and trees, or intensive green roofs, remove air pollutants to a greater extent and are advisable to implement on existing, retrofitted or new buildings. PM is most effectively captured by pines. The small Pinus strobus ‘Nana’, Pinus mugho var. pumilio, Pinus mugho ‘Slowmound’ and Pinus pumila ‘Dwarf Blue’ are good candidates for intensive green roofs. Drought tolerant, deciduous broadleaved trees with low biogenic volatile organic compound emissions including Japanese Maple or Acer palmatum ‘Shaina’ and ‘Mikawa-Yatsubusa’ are options to reduce O3 levels. Magnolias are tolerant to NO2 and it is important in their metabolic pathways. The small cold-tolerant Magnolia ‘Genie’ is a good option to remove NO2 in urban settings and to indirectly reduce O3 formation. Given the emissions by Montreal businesses' wood ovens, calculations performed based on their respective complex roof areas obtained via Google Earth Pro indicates 88% Pinus mugho var. pumilio roof coverage can annually remove 92.37 kg of PM10 of which 35.10 kg is PM2.5. The removal rates are 4.00 g/m2 and 1.52 g/m2 for PM10 and PM2.5, respectively. This paper provides insight to addressing air pollution through urban rooftop greening.

Multiple cross-sectional studies indicated an association between hypertension and road traffic noise and they were recently synthetized in a WHO systematic evidence review. However, recent years have seen a growing body of high-quality, large-scale research, which is missing from the WHO review. Therefore, we aimed to close that gap by conducting an updated systematic review and meta-analysis on the exposure-response relationship between residential road traffic noise and the risk of hypertension in adults. Studies were identified by searching MEDLINE, EMBASE, the Internet, conference proceedings, reference lists, and expert archives in English, Russian, and Spanish through August 5, 2017. The risk of bias for each extracted estimate and the overall quality of evidence were evaluated using a list of predefined safeguards against bias related to different study characteristics and the Grading of Recommendations Assessment, Development and Evaluation system, respectively. The inverse variance heterogeneity (IVhet) model was used for meta-analysis. The possibility of publication bias was evaluated by funnel and Doi plots, and asymmetry in these was tested with Egger's test and the Luis Furuya-Kanamori index, respectively. Sensitivity analyses included leave-one-out meta-analysis, subgroup meta-analysis with meta-regressions, and non-linear exposure-response meta-analysis. Based on seven cohort and two case-control studies (n = 5 514 555; 14 estimates; Lden range ≈ 25–90 dB(A)), we found “low” evidence of RR per 10 dB(A) = 1.018 (95% CI: 0.984, 1.053), moderate heterogeneity (I2 = 46%), and no publication bias. In the subgroup of cohort studies, we found “moderate” evidence of RR per 10 dB(A) = 1.018 (95% CI: 0.987, 1.049), I2 = 31%, and no publication bias. In conclusion, residential road traffic noise was associated with higher risk of hypertension in adults, but the risk was lower than previously reported in the systematic review literature.

With the development of society and the economy, many Chinese cities are shrouded in pollution haze for much of the year. Scientific studies have identified various adverse effects of air pollutants on human beings. However, the relationships between air pollution and blood lipid levels are still unclear. The objective of this study is to explore the short and long-term effects of air pollution on eight blood lipid markers among elderly hypertension inpatients complicated with or without type 2 diabetes (T2D). Blood lipid markers which met the pre-established inclusion criteria were exported from the medical record system. Air pollution data were acquired from the official environmental protection website. Associations between the air quality index and the blood lipid indexes were analyzed by one-way ANOVA and further Bonferroni correction. In an exposure time of 7 days or longer, blood lipid markers were somewhat affected by poor air quality. However, the results could not predict whether atherosclerosis would be promoted or inhibited by poorer air condition. Changes of blood lipid markers of hypertension inpatients with or without T2D were not completely the same, but no blood lipid markers had an opposite trend between the two populations. The air quality index was associated with changes to blood lipid markers to some extent in a population of hypertension inpatients with or without T2D. Further studies are needed to investigate the potential mechanism by which air pollutants induce blood lipids changes.

We explore how the analysis of web-based data, such as Twitter and Google Trends, can be used to assess the social relevance of an environmental accident. The concept and methods are applied in the shutdown of drinking water supply at the city of Toledo, Ohio, USA. Toledo's notice, which persisted from August 1 to 4, 2014, is a high-profile event that directly influenced approximately half a million people and received wide recognition. The notice was given when excessive levels of microcystin, a byproduct of cyanobacteria blooms, were discovered at the drinking water treatment plant on Lake Erie. Twitter mining results illustrated an instant response to the Toledo incident, the associated collective knowledge, and public perception. The results from Google Trends, on the other hand, revealed how the Toledo event raised public attention on the associated environmental issue, harmful algal blooms, in a long-term context. Thus, when jointly applied, Twitter and Google Trend analysis results offer complementary perspectives. Web content aggregated through mining approaches provides a social standpoint, such as public perception and interest, and offers context for establishing and evaluating environmental management policies.

Since 2007, the outbreak of green tides has become the most serious ecological problem in the Yellow Sea. In this study, a new method was used to identify green tides in multi-source satellite data from 2007 to 2020, and the relationship between the conditions necessary for green tide dissipation and other environmental factors was discussed. We found a “wavy” trend of green tide scales over the 14-year dissipation period. The dissipation direction was influenced by sea surface wind (SSW) and sea surface circulation (SSC). Under the action of northeast moving SSW and SSC, green tides move away from the shore and drift northward; under the action of northwest or southwest moving SSW and SSC, they moved towards the shore and drift southward. The date of dissipation was influenced by sea surface temperature (SST) and precipitation, and high SST accelerated the process of green tide dissipation, while precipitation slowed it down.