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Abstract Background Epidemiological evidence on the association between short-term exposure to fine particulate matter (PM 2.5) air pollution and acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is limited in China. Objectives To explore the associations between PM 2.5 and AECOPD in Yancheng, China from 2015 to 2017. Methods In this time-series study, we used a generalized linear model with quasi- Poisson regression to investigate the association between PM 2.5 and AECOPD admitted in two major hospitals in Yancheng. We tested the robustness of the associations using two-pollutant models and examined the potential effect modification by age, gender and season via stratification analyses. Lastly, we fitted the concentration-response curves. Results We identified a total of 4761 AECOPD inpatients during the study period. The average daily-mean PM 2.5 concentration was 45.2 μg/m3. Each 10 μg/m3 increase in PM 2.5 concentration on the concurrent day of the onset of AECOPD was associated with a 1.05% (95% confidence interval: 0.14%, 1.96%) increase in AECOPD. The association was robust to the adjustment of ozone, but not to sulfur dioxide, nitrogen dioxide, and carbon monoxide. The association was larger in females, elderly patients, and was restricted within the cold season, but all between-group differences were insignificant. The concentration-response relationship curves were generally linear but flatted at concentrations over 40 μg/m3. Conclusions This study demonstrated a higher risk of AECOPD associated with present-day PM 2.5 exposure in a Chinese city. We further provided important information on lag patterns, susceptible subgroups, sensitive seasons, as well as the characteristics of the concentration-response relationship curves. Graphical abstract Unlabelled Image Highlights • PM 2.5 was associated with an increased risk of acute exacerbation of COPD. • Females and older COPD patients were more susceptible to PM 2.5. • COPD patients were more sensitive to PM 2.5 in cold season. [ABSTRACT FROM AUTHOR]

Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design. Unlabelled Image • A human-centred perspective for street thermal comfort assessment with eye-level images • Fine scale neighbourhood heat vulnerability index was developed. • Low thermal comfort street sections in high heat vulnerable neighbourhoods were prioritised. • The framework can be adapted by decision makers to enhance the climate resilience of streets. [ABSTRACT FROM AUTHOR]

Abstract Due to the intensity of urban development around the world, there is an increasing body of studies attempting to investigate urban heat island (UHI) in various spatial and temporal scales. In surface heat urban island (SUHI) studies, extended periods of time, broader regions and local government area (LGA) level have become more crucial and will shed light on causes of UHI. Moreover, the spatial pattern and structure of SUHI will be useful for policy-makers to develop mitigation strategies. This study focused on three objectives. Firstly, analyzing land surface temperature (LST), normalized difference built-up (NDBI) and vegetation (NDVI) indices. Secondly, investigating interrelationships among LST, NDVI, and NDBI. Thirdly, identifying LST patterns in the Melbourne metropolitan area. These objectives were achieved through three different methods. The modified automatic mapping method for the first objective, the correlation analysis for the second, and spatial statistical methods for the third. The methodological innovations of this study were considering LGA in interrelationship analysis among LST, NDBI and NDVI, and calculation of NDVI for each acquisition date. The results indicated that the clustering pattern of LST expanded toward the north-west and south-east during the period of the study. Furthermore, the north-west part of the city has the highest positive (0.6) correlation between NDBI and LST, and the south-east part of the city has the lowest negative (−0.8) correlation between NDVI and LST. The most significant increase and decrease in mean LST happened respectively from January 6th to 22nd 2017, and January 14th to 30th January 2014. The temperature degree altered from 19.61 °C to 27.86 °C in inner western suburbs, and from 35.49 °C to 26.88 °C in most LGA's. These findings are critical for planners to localize UHI mitigation action plans, target hot spots in LGA's and allocate resources to respond to the adverse effect of UHI. Graphical abstract Unlabelled Image Highlights • Time-series satellite imagery and spatial statistical used to determine the LST spatial structure at the local government level. • LST calculated by the modified mapping method and NDVI calculated for each acquisition dates from Landsat satellite images. • Overall, clustering patterns of LST expanded toward the north-west(NW) and south-east(SE) in Melbourne • NW part has the highest positive correlation between NDBI and LST; SE part has lowest negative correlation for NDVI and LST [ABSTRACT FROM AUTHOR]

Due to the lack of wastewater treatment facility in Pakistan, the wastewater is directly discharged via urban drains, which might cause a high load of contaminants of emerging concerns and potential environmental risks. The present study focused on the occurrence and risk assessment of 52 pharmaceuticals and personal care products (PPCPs) of diversified classes in the water and sediment samples of urban drains and canal of Lahore, Pakistan. Non-steroidal anti-inflammatory drugs were the predominant PPCPs detected in the wastewater of urban drains and surface water of canal. The highest concentration was observed for acetaminophen, with median concentration of 13,880 ng/L followed by caffeine with median concentration of 6200 ng/L. Antibiotics were the predominant PPCPs in the sediment samples with highest concentration of ofloxacin (median value of 1980 μg/kg) followed by ciprofloxacin and oxytetracycline. Spatial variation showed that the population density has significant correlation with the level of many PPCPs in surface water while one of the drainage systems is affected by the direct wastewater discharge from the nearby industrial area. Ecological risk assessment in terms of risk quotient revealed that most of the PPCPs may cause high risk to the aquatic community. This high risk may lead to further contamination of food and crops, therefore enforcement of environmental legislations for treatment of wastewater is recommended. Unlabelled Image • Occurrence of 52 PPCPs in wastewater and surface water in Pakistan was studied. • NSAIDs were dominated in aqueous sample while antibiotics were rich in sediment. • High risk by most of the PPCPs was raised to the aquatic community. • Treatment of wastewater is suggested before its discharge into surface water. [ABSTRACT FROM AUTHOR]

Sulfamethoxazole (SMX) is a sulfonamide antibiotic, widely used as curative and preventive drug for human, animal, and aquaculture bacterial infections. Its residues have been ubiquitously detected in the surface waters and sediments. In the present study, SMX dissipation and kinetics was studied in the natural water samples from Jiulong River under simulated complex natural conditions as well as conditions to mimic various biotic and abiotic environmental conditions in isolation. Structural equation modeling (SEM) by employing partial least square technique in path coefficient analysis was used to investigate the direct and indirect contributions of different environmental factors in the natural attenuation of SMX. The model explained 81% of the variability in natural attenuation as a dependent variable under the influence of sole effects of direct photo-degradation, indirect photo-degradation, hydrolysis, microbial degradation and bacterial degradation. The results of SEM suggested that the direct and indirect photo-degradation were the major pathways in the SMX natural attenuation. However, other biotic and abiotic factors also play a mediatory role during the natural attenuation and other processes. Furthermore, the potential transformation products of SMX were identified and their toxicity was evaluated. [ABSTRACT FROM AUTHOR]

Micropollutants have become of great concern, because of their disrupting effects on the structure and function of microbial communities. However, little is known about the relative importance of trace micropollutants on the aquatic prokaryotic communities as compared to the traditional physico-chemical characteristics, especially at different spatial dimensions. Here, we investigated free-living (FL) and particle-associated (PA) prokaryotic communities in a subtropical water reservoir, China, across seasons at horizontal (surface water) and vertical (depth-profile) scales by using 16S rRNA gene amplicon sequencing. Our results showed that the shared variances of physico-chemicals and micropollutants explained majority of the spatial variations in prokaryotic communities, suggesting a strong joint effect of the two abiotic categories on reservoir prokaryotic communities. Micropollutants appeared to exert strong independent influence on the core sub-communities (i.e., abundant and wide-spread taxa) than on the satellite (i.e., less abundant and narrow-range taxa) counterparts. The pure effect of micropollutants on both core and satellite sub-communities from FL and PA fractions was ~1.5 folds greater than that of physico-chemical factors at the horizontal scale, whereas an opposite effect was observed at the vertical scale. Moreover, eight micropollutants including anti-fungal agents, antibiotics, bisphenol analogues, stimulant and UV-filter were identified as the major disrupting compounds with strong associations with core taxa of typical freshwater prokaryotes. Altogether, we concluded that the ecological disrupting effects of micropollutants on prokaryotic communities may vary along horizontal and vertical dimensions in freshwater ecosystems. Unlabelled Image • Physico-chemicals and micropollutants had joint effects on prokaryotic communities. • Micropollutants had stronger effects on the surface water than vertical communities. • Micropollutants exerted stronger influence on the core than satellite groups. • Lifestyle-dependent responses to micropollutants were observed. • Eight micropollutants had strong associations with abundant core taxa. [ABSTRACT FROM AUTHOR]