Due to the increase of the human population and the rapid industrial growth in the past few decades, air quality monitoring is essential to assess the pollutant levels of an area. However, monitoring air quality in a high-density area like Sunway City, Selangor, Malaysia is challenging due to the limitation of the local monitoring network. To establish a comprehensive data for air pollution in Sunway City, a mobile monitoring campaign was employed around the city area with a duration of approximately 6 months, from September 2018 to March 2019. Measurements of air pollutants such as carbon dioxide (CO₂) and nitrogen dioxide (NO₂) were performed by using mobile air pollution sensors facilitated with a GPS device. In order to acquire a more in-depth understanding on traffic-related air pollution, the measurement period was divided into two different time blocks, which were morning hours (8 a.m.–12 p.m.) and afternoon hours (3 p.m.–7 p.m.). The data set was analysed by splitting Sunway City into different zones and routes to differentiate the conditions of each region. Meteorological variables such as ambient temperature, relative humidity, and wind speed were studied in line with the pollutant concentrations. The air quality in Sunway City was then compared with various air quality standards such as Malaysian Air Quality Standards and World Health Organisation (WHO) guidelines to understand the risk of exposure to air pollution by the residence in Sunway City.

Elevated inorganic arsenic concentrations in groundwater has become a major public and environmental health concern in different parts of the world. Currently, As-contaminated groundwater issue in many countries and regions is a major topic for publications at global level. However, there are many regions worldwide where the problem has still not been resolved or fully understood due to inadequate hydrogeochemical investigations. Hence, this study evaluates for the first time the hydrogeochemical behavior of the arid and previously unexplored inland basin of Sirjan Plain, south east (SE) Iran, in order to assess the controlling factors which influence arsenic (As) mobility and its distribution through groundwater resources. Total inorganic arsenic concentration was measured using inductive-coupled plasma optical emission spectrometry (ICP-OES). Arsenic content in groundwater of this region ranged between 2.4 and 545.8 μg/L (mean value: 86.6 μg/L) and 50% of the samples exceeded the World Health Organization (WHO) guideline value of 10 μg/L in drinking water. Groundwater was mainly of Na-Cl type and alkaline due to silicate weathering, ion exchange and evaporation in arid conditions. Elevated As concentrations were generally observed under weakly alkaline to alkaline conditions (pH > 7.4). Multivariate statistical analysis including cluster analysis and bi-plot grouped As with pH and HCO3 and demonstrated that the secondary minerals including oxyhydroxides of Fe are the main source of As in groundwater in this region. The desorption of As from these mineral phases occurs under alkaline conditions in oxidizing arid environments thereby leading to high levels of As in groundwater. Moreover, evaporation, ion exchange and saltwater intrusion were the secondary processes accelerating As release and its mobility in groundwater. Based on the results of this study, desorption of As from metal oxy-hydroxides surfaces under alkaline conditions, evaporation and intrusion of As-rich saline water are considered to be the major factors causing As enrichment in arid inland basins such as those in southeast Iran. This study proposes the regular monitoring and proper groundwater management practices to mitigate high levels of arsenic in groundwater and related drinking water wells of Sirjan Plain.

Urban population exposure to tropospheric ozone is a serious health concern in Europe countries. Although there are insufficient evidence to derive a level below which ozone has no effect on mortality WHO (World Health Organization) uses SOMO35 (sum of means over 35 ppb) in their health impact assessments. Is this paper, the artificial neural network (ANN) approach was used to forecast SOMO35 at the national level for a set of 24 European countries, mostly EU members. Available ozone precursors’ emissions, population and climate data for the period 2003–2013 were used as inputs. Trend analysis had been performed using the linear regression of SOMO35 over time, and it has demonstrated that majority of the studied countries have a decreasing trend of SOMO35 values.The created models have made majority of predictions (≈60%) with satisfactory accuracy (relative error <20%) on testing, while the best performing model had R² = 0.87 and overall relative error of 33.6%. The domain of applicability of the created models was analyzed using slope/mean ratio derivate from the trend analysis, which was successful in distinguishing countries with high from countries with low prediction errors. The overall relative error was reduced to <14%, after the pool of countries was reduced based on the abovementioned criterion.

While increasing evidence suggested that PM₂.₅ is the most harmful fraction of the particle pollutants, the health effects of coarse particles (PM₁₀–₂.₅) have been inconclusive, especially on cerebrovascular diseases, we thus evaluated the effects of PM₁₀, PM₂.₅, and PM₁₀–₂.₅ on stroke mortality in six Chinese subtropical cities using generalized additive models. We also conducted random-effects meta-analyses to estimate the overall effects across the six cities. We found that PM₁₀, PM₂.₅, and PM₁₀₋₂.₅ were significantly associated with stroke mortality. Each 10 μg/m³ increase of PM₁₀, PM₂.₅ and PM₁₀₋₂.₅ (lag03) was associated with an increase of 1.88% (95% CI: 1.37%, 2.39%), 3.07% (95% CI: 2.35%, 3.79%), and 5.72% (95% CI: 3.82%, 7.65%) in overall stroke mortality. Using the World Health Organization's guideline as reference concentration, we estimated that 3.21% (95% CI: 1.65%, 3.01%) of stroke mortality (corresponding to 1743 stroke mortalities, 95% CI: 896, 1633) were attributed to PM₁₀, 5.57% (95% CI: 0.50%, 1.23%) stroke mortality (3019, 95% CI: 2286, 3777) were attributed to PM₂.₅, and 2.02% (95% CI: 1.85%, 3.08%) of stroke mortality (1097, 95% CI: 1005, 1673) could be attributed to PM₁₀₋₂.₅. Our analysis indicates that both PM₂.₅ and PM₁₀₋₂.₅ are important risk factors of stroke mortality and should be considered in the prevention and control of stroke in the study area.

In China, ozone pollution shows an increasing trend and becomes the primary air pollutant in warm seasons. Leveraging the air quality monitoring network, a random forest model is developed to predict the daily maximum 8-h average ozone concentrations ([O₃]MDA₈) across China in 2015 for human exposure assessment. This model captures the observed spatiotemporal variations of [O₃]MDA₈ by using the data of meteorology, elevation, and recent-year emission inventories (cross-validation R² = 0.69 and RMSE = 26 μg/m³). Compared with chemical transport models that require a plenty of variables and expensive computation, the random forest model shows comparable or higher predictive performance based on only a handful of readily-available variables at much lower computational cost. The nationwide population-weighted [O₃]MDA₈ is predicted to be 84 ± 23 μg/m³ annually, with the highest seasonal mean in the summer (103 ± 8 μg/m³). The summer [O₃]MDA₈ is predicted to be the highest in North China (125 ± 17 μg/m³). Approximately 58% of the population lives in areas with more than 100 nonattainment days ([O₃]MDA₈>100 μg/m³), and 12% of the population are exposed to [O₃]MDA₈>160 μg/m³ (WHO Interim Target 1) for more than 30 days. As the most populous zones in China, the Beijing-Tianjin Metro, Yangtze River Delta, Pearl River Delta, and Sichuan Basin are predicted to be at 154, 141, 124, and 98 nonattainment days, respectively. Effective controls of O₃ pollution are urgently needed for the highly-populated zones, especially the Beijing-Tianjin Metro with seasonal [O₃]MDA₈ of 140 ± 29 μg/m³ in summer. To the best of the authors’ knowledge, this study is the first statistical modeling work of ambient O₃ for China at the national level. This timely and extensively validated [O₃]MDA₈ dataset is valuable for refining epidemiological analyses on O₃ pollution in China.

This article comments on the current reality of particulate matter (PM) concentrations breathed by commuters on subway train platforms and considers what can be done to improve air quality underground. We propose the introduction of a targeted, color-coded approach to the problem, based on the methodology of the World Health Organisation and designed to encourage transport authorities to aim for progressive PM reductions. The method defines thresholds that cascade down through bands of decreasing PM concentrations towards the ideal WHO Air Quality Guideline of PM₂.₅ annual mean level of 10 μg m⁻³, where negative health effects of long term particle inhalation are minimal.

In China, over 1.3 billion people have high health risks associated with exposure to ambient fine particulate matter (PM2.5) that exceeds the World Health Organization (WHO) Air Quality Guidelines (AQG). The PM2.5 mass concentrations from 1382 national air quality monitoring stations in 367 cities, between January 2014 and December 2016, were analyzed to estimate the health burden attributable to ambient PM2.5 across China. The integrated exposure-response model was applied to estimate the relative risks of disease-specific mortality. Disease-specific mortality baselines in province-level administrative units were adjusted by the national mortality baseline to better reveal the spatial inequality of the health burden associated with PM2.5. Our study suggested that PM2.5 in 2015 contributed as much as 40.3% to total stroke deaths, 33.1% to acute lower respiratory infection (ALRI, <5yr) deaths, 26.8% to ischemic heart disease (IHD) deaths, 23.9% to lung cancer (LC) deaths, 18.7% to chronic obstructive pulmonary disease (COPD) deaths, 30.2% to total deaths combining IHD, stroke, COPD, and LC, 15.5% to all cause deaths. The population weighted average (PWA) attributable mortality rates (10−5 y−1) were 112.0 in current year analysis, and 124.3 in 10-year time lag analysis. The Mortality attributable to PM2.5 in 10-year time lag analysis (1.7 million) was 12% higher than the current year analysis (1.5 million). Our study also estimated site-specific annual PM2.5 concentrations in scenarios of achieving WHO interim targets (ITs) and AQG. The mortality benefits will be 24.0%, 44.8%, 70.8%, and 85.2% of the total current mortalities (1.5 million) when the PWA PM2.5 concentrations in China meets the WHO IT-1, IT-2, IT-3, and AQG, respectively. We expect air quality modeling and cost-benefits analysis of emission reduction scenarios and corresponding health benefits in meeting the site-specific annual PM2.5 concentrations (WHO IT-1, IT-2, IT-3, and AQG) this study raised.

In Ireland, the land application of biosolids is the preferred option of disposing of municipal sewage waste. Biosolids provide nutrients in the form of nitrogen, phosphorus, potassium and increases organic matter. It is also an economic way for a country to dispose of its municipal waste. However, biosolids may potentially contain a wide range of pathogens, and following rainfall events, may be transported in surface runoff and pose a potential risk to human health. Thus, a quantitative risk assessment model was developed to estimate potential pathogens in surface water and the environmental fate of the pathogens following dilution, residence time in a stream, die-off rate, drinking water treatment and human exposure. Surface runoff water quality data was provided by project partners. Three types of biosolids, anaerobically digested (AD), lime stabilised (LS), and thermally dried (TD)) were applied on micro plots. Rainfall was simulated at three time intervals (24, 48 and 360 h) following land application. It was assumed that this water entered a nearby stream and was directly abstracted for drinking water. Consumption data for drinking water and body weight was obtained from an Irish study and assigned distributions. Two dose response models for probability of illness were considered for total and faecal coliform exposure incorporating two different exposure scenarios (healthy populations and immuno-compromised populations). The simulated annual risk of illness for healthy populations was below the US EPA and World Health Organisation tolerable level of risk (10⁻⁴ and 10⁻⁶, respectively). However, immuno-compromised populations may still be at risk as levels were greater than the tolerable level of risk for that subpopulation. The sensitivity analysis highlighted the importance of residence time in a stream on the bacterial die-off rate.

In 2014, as an attempt to address the Zika health crisis by controlling the mosquito population, Brazil took the unprecedented action of applying a chemical larvicide, pyriproxyfen, to drinking water sources. The World Health Organization has established an acceptable daily intake of pyriproxyfen to be 100 μg per kg of body weight per day, but studies have demonstrated that at elevated doses (>5000 mg/kg), there are adverse effects in mice, rats and dogs. To better understand the potential developmental toxicity of pyriproxyfen, we utilized the embryonic zebrafish. Our results demonstrate that the concentration resulting in 50% of animals presenting adverse morphological effects (EC50), including craniofacial defects, was 5.2 μM for daily renewal exposure, and above this concentration, adverse behavioral effects were also observed in animals that followed a static exposure regimen. Thus, zebrafish data suggest that the developmental toxicity of pyriproxyfen may not be limited to insects.

We examined and compared PM2.5 concentrations in urban and the surrounding regions, and further investigated the impact of urbanization on urban PM2.5 concentrations at the Chinese prefectures. Annual PM2.5 concentrations in most prefectures were greater than 10 μg/m3, the air quality guideline of the World Health Organization. Those prefectures were mainly distributed along the east coast and southeast of Sichuan province; The urban PM2.5 concentrations (UrbanPM2.5) in 85 cities were greater than (>10 μg/m3) those in the surrounding area. Those cities were mainly located in the Beijing–Sichuan and Shanghai–Guangxi belts. In addition, UrbanPM2.5 was less than (<0 μg/m3) that in surrounding areas in only 41 prefectures, which were located in western China or nearby mega cities; Significant positive correlations were found between UrbanPM2.5 and urban population (R2 = 0.99, P < 0.05), and between UrbanPM2.5 and urban second industry fraction (R2 = 0.71, P < 0.05), suggesting that urbanization had considerable impact on PM2.5 concentrations.