Marine debris has become a major form of pollution and a serious ecosystem health concern. The present study evaluates the accumulation, origin, and fate of debris in intertidal coral habitats of Mumbai-one of the world's highly populated coastal cities on the west coast of India. Predominantly, seven hermatypic coral species belonging to seven genera and five families were identified and mainly represented by Pseudosidastrea, Porites, and Bernardpora. In terms of number, the mean density of marine debris was 1.60 ± 0.13 SE items/m², which is higher than the global average. The mean density of plastic debris was 1.46 ± 0.14 SE items/m². Approximately 9% of total coral colonies were in physical contact with debris, and 22% of these colonies showed visible signs of partial bleaching. Single use plastic bags and wrappers were dominant plastic debris. The study area was characterized as ‘very poor cleanliness’ according to the Beach Quality Indexes, which include the Clean Coast Index, General Index, and Hazardous Items Index. The numerical model indicates the influence of river discharge and probable areas of plastic accumulation with high tidal currents in this region, maneuvering the spatial advection of litter in the nearshore areas. Combined analysis of ground-truthing and model simulation implies that the possible contributing sources of litter were representatives of land-based and sea-originated. The overall results point to increasing anthropogenic stressors threatening coastal coral communities, including marine debris pollution. It is advocated to adopt an integrated coastal zone management approach supported by coordinated policy frameworks could guide the mitigation of the debris footprint in coastal environments.

Atmospheric bioaerosols contain live and dead biological components that can enter the human respiratory tract (HRT) and affect human health. Here, the total microorganisms in a coastal megacity, Qingdao, were characterized on the basis of long-term observations from October 2013 to January 2021. Particular attention was given to the size dependence of inhalable bioaerosols in concentration and respiratory deposition in different populations on foggy and hazy days. Bioaerosol samples stained with 4,6-diamidino-2-phenylindole (DAPI) were selected to measure the total airborne microbe (TAM) concentrations with an epifluorescence microscope, while a multiple-path particle dosimetry model was employed to calculate respiratory deposition. The mean TAM concentrations in the particle size range of 0.65–1.1 μm (TAM₀.₆₅–₁.₁) were 1.23, 2.02, 1.60 and 2.33 times those on sunny reference days relative to the corresponding values on days with slight, mild, moderate and severe levels of haze, respectively. The mean concentration of TAMs in the particle size range of 0.65–2.1 μm (TAM₀.₆₅–₂.₁) on severely hazy days was (2.02 ± 3.28) × 10⁵ cells/m³, with a reduction of 4.16% relative to that on the reference days. The mean TAM₀.₆₅–₂.₁ concentration changed from (1.50 ± 1.37) × 10⁵ cells/m³ to (1.76 ± 1.36) × 10⁵ cells/m³, with TAM₀.₆₅–₁.₁ increasing from (7.91 ± 7.97) × 10⁴ cells/m³ to (1.76 ± 1.33) × 10⁵ cells/m³ on days with light fog days and medium fog, respectively. The modeling results showed that the majority of TAM₀.₆₅–₂.₁ deposition occurred in the extrathoracic (ET) region, followed by the alveolar (AL) region. When different populations were examined separately, the deposition doses (DDs) in adult females and in children ranked at the minimum value (6.19 × 10³ cells/h) and maximum value (1.08 × 10⁴ cells/h), respectively. However, the inhalation risks on polluted days, such as hazy, foggy and mixed hazy–foggy (HF) days, were still below the threshold for adverse impacts on human health.

The coastal megacity Shanghai is located in the center of the Yangtze River Delta, a dominant flame retardants (FRs) production region in China, especially for organophosphate esters (OPEs). This prompted us to investigate occurrence and seasonal changes of atmospheric OPEs in Shanghai, as well as to evaluate their sources, environmental behavior and fate as a case study for global coastal regions. Atmospheric gas and particle phase OPEs were weekly collected at two coastal sites - the emerging town Lingang New Area (LGNA), and the chemical-industry zone Jinshan Area (JSA) from July 2016–June 2017. Total atmospheric concentrations of the observed OPEs were significantly higher in JSA (median of 1800 pg m⁻³) than LGNA (median of 580 pg m⁻³). Tris(1-chloro-2-propyl) phosphate (TCPP) was the most abundant compound, and the proportion of three chlorinated OPEs were higher in the particle phase (55%) than in the gas phase (39%). The year-round median contribution of particle phase OPEs was 33%, which changed strongly with seasons, accounting for 10% in summer in contrast to 62% in winter. Gas and particle phase OPEs in JSA exhibited significant correlations with inverse of temperature, respectively, indicating the importance of local/secondary volatilization sources. The estimated fluxes of gaseous absorption were almost 2 orders of magnitude higher than those of particle phase deposition, which could act as sources of organic phosphorus to coastal and open ocean waters.

Increased interest in backyard food production has drawn attention to the risks associated with urban trace element contamination, in particular lead (Pb) that was used in abundance in Pb-based paints and gasoline. Here we examine the sources, pathways and risks associated with environmental Pb in urban gardens, domestic chickens and their eggs. A suite of other trace element concentrations (including As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn) are reported from the sampled matrices. Sixty-nine domestic chickens from 55 Sydney urban gardens were sampled along with potential sources (feed, soil, water), blood Pb concentrations and corresponding concentrations in eggs. Age of the sampled chickens and house age was also collected. Commercial eggs (n = 9) from free range farms were analysed for comparative purposes. Study outcomes were modelled using the large Australian VegeSafe garden soil database (>20,000 samples) to predict which areas of inner-city Sydney, Melbourne and Brisbane are likely to have soil Pb concentrations unsuitable for keeping backyard chickens. Soil Pb concentrations was a strong predictor of chicken blood and egg Pb (p=<0.00001). Almost 1 in 2 (n = 31/69) chickens had blood Pb levels >20 μg/dL, the level at which adverse effects may be observed. Older homes were correlated with higher chicken blood Pb (p = 0.00002) and egg Pb (p = 0.005), and younger chickens (<12 months old) had greater Pb concentrations, likely due to increased Pb uptake during early life development. Two key findings arose from the study data: (i) in order to retain chicken blood Pb below 20 μg/dL, soil Pb needs to be < 166 mg/kg; (ii) to retain egg Pb < 100 μg/kg (i.e. a food safety benchmark value), soil Pb needs to be < 117 mg/kg. These concentrations are significantly lower than the soil Pb guideline of 300 mg/kg for residential gardens. This research supports the conclusion that a large number of inner-city homes may not be suitable for keeping chickens and that further work regarding production and consumption of domestic food is warranted.

Atmospheric peroxyacetyl nitrate (PAN) and ozone (O₃) are two typical indicators for photochemical pollution that have adverse effects on the ecosystem and human health. Observation networks for these pollutants have been expanding in developed regions of China, such as North China Plain (NCP) and Pearl River Delta (PRD), but are sparse in Yangtze River Delta (YRD), meaning their concentration and influencing factors remain poorly understood. Here, we performed a one-year measurement of atmospheric PAN, O₃, particulate matter with aerodynamic diameter smaller than 2.5 μm (PM₂.₅), nitrogen oxides (NOₓ), carbon monoxide (CO), and meteorological parameters from December 2016 to November 2017 in Shanghai. Overall, high hourly maximum PAN and O₃ were found to be 7.0 and 185 ppbv in summer, 6.2 and 146 ppbv in autumn, 5.8 and 137 ppbv in spring, and 6.0 and 76.7 ppbv in winter, respectively. Continental air masses probably carried atmospheric pollutants to the sampling site, while frequent maritime winds brought in less polluted air masses. Furthermore, positive correlations (R: 0.72–0.85) between PAN and O₃ were found in summer, indicating a predominant role of photochemistry in their formation. Unlike in summer, weak or no correlations between PAN and O₃ were featured during the other seasons, especially in winter, due to their different loss pathways. Unexpectedly, positive correlations between PAN and PM₂.₅ were found in all seasons. During summer, moderate correlation could be attributed to the strong photochemistry acting as a common driver in the formation of secondary aerosols and PAN. During winter, high PM₂.₅ might promote PAN production through HONO production, hence resulting in a good positive correlation. Additionally, the loss of PAN by thermal decomposition (TPAN) only accounted for a small fraction (ca. 1%) of the total (PAN + TPAN) during a typical winter episode, while it significantly reached 14.4 ppbv (71.1% of the total) in summer.

Traffic source–dominated volatile organic compound (VOC) samples were collected during four time-intervals in a day (Ⅰ: 7:30–10:30, Ⅱ: 11:00–14:00, Ⅲ: 16:30–19:30, and Ⅳ: 20:00–23:00) in a tunnel in summer, 2019, in Xi’an, China. The total measured VOC (TVOC) in periods Ⅰ and Ⅲ (rush hours, 107.2 ± 8.2 parts per billion by volume [ppbv]) was 1.8 times that in periods Ⅱ and Ⅳ (non-rush hours, 58.6 ± 13.8 ppbv), consistent with the variation in vehicle numbers in the tunnel. The considerably elevated ethane and ethylbenzene levels could have been attributed to emissions from compressed natural gas vehicles and the rapid development of methanol-fueled taxis in Xi’an in 2019. The mixing ratios of benzene, toluene, ethylbenzene, and xylenes (BTEX) contributed 9.4%–12.7% to TVOCs, and the contributions were nearly 40% higher in periods Ⅰ and Ⅲ than in Ⅱ and Ⅳ, indicating that BTEX levels were strongly affected by vehicle emissions. The indicators of motor vehicle emission, namely ethylene, propylene, toluene, m/p-xylenes, o-xylene, and propane, contributed to more than half of the ozone formation potential in this study. The noncarcinogenic risks of VOCs in this study were within the international safety standard, whereas the carcinogenic risks exceeded the standard by 2.3–4.6 times, suggesting that carcinogenic risks were more serious than noncarcinogenic risks. VOCs presented 2.2 and 1.4 times noncarcinogenic and carcinogenic risks during rush hours than during non-rush hours, respectively. Notably, the carcinogenic risk in period Ⅳ was comparable with that in period Ⅲ; however, the vehicle numbers and VOC mixing ratios were the lowest at night, which may have attributed to the increasing number and proportion of methanol M100-fueled vehicles in the tunnel. Therefore, VOCs emitted by new energy vehicles should also be seriously considered while evaluating fossil fuel vehicle emissions.

The determination of both stable nitrogen (δ¹⁵N–NO₃⁻) and stable oxygen (δ¹⁸O–NO₃⁻) isotopic signatures of nitrate in PM₂.₅ has shown potential for an approach of assessing the sources and oxidation pathways of atmospheric NOx (NO+NO₂). In the present study, daily PM₂.₅ samples were collected in the megacity of Beijing, China during the winter of 2017–2018, and this new approach was used to reveal the origin and oxidation pathways of atmospheric NOx. Specifically, the potential of field δ¹⁵N–NO₃⁻ signatures for determining the NOx oxidation chemistry was explored. Positive correlations between δ¹⁸O–NO₃⁻ and δ¹⁵N–NO₃⁻ were observed (with R² between 0.51 and 0.66, p < 0.01), and the underlying environmental significance was discussed. The results showed that the pathway-specific contributions to NO₃⁻ formation were approximately 45.3% from the OH pathway, 46.5% from N₂O₅ hydrolysis, and 8.2% from the NO₃+HC channel based on the δ¹⁸O-δ¹⁵N space of NO₃⁻. The overall nitrogen isotopic fractionation factor (εN) from NOx to NO₃⁻ on a daily scale, under winter conditions, was approximately +16.1‰±1.8‰ (consistent with previous reports). Two independent approaches were used to simulate the daily and monthly ambient NOx mixtures (δ¹⁵N-NOx), respectively. Results indicated that the monthly mean values of δ¹⁵N-NOx compared well based on the two approaches, with values of −5.5‰ ± 2.6‰, −2.7‰ ± 1.9‰, and −3.2‰ ± 2.2‰ for November, December, and January (2017–2018), respectively. The uncertainty was in the order of 5%, 5‰ and 5.2‰ for the pathway-specific contributions, the εN, and δ¹⁵N-NOx, respectively. Results also indicated that vehicular exhaust was the key contributor to the wintertime atmospheric NOx in Beijing (2017–2018). Our advanced isotopic perspective will support the future assessment of the origin and oxidation of urban atmospheric NOx.

This research apportioned size-resolved particulate matter (PM) contributions in a megacity in northern China based on a full year of measurements of both inorganic and organic markers. Ions, elements, carbon fractions, n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes and steranes in 9 p.m. size fractions were analyzed. High molecular weight PAHs concentrated in fine PM, while most other organic compounds showed two peaks. Both two-way and three-way receptor models were used for source apportionment of PM in different size ranges. The three-way receptor model gave a clearer separation of factors than the two-way model, because it uses a combination of chemical composition and size distributions, so that factors with similar composition but distinct size distributions (like more mature and less mature coal combustion) can be resolved. The three-way model resolved six primary and three secondary factors. Gasoline vehicles and coal and biomass combustion, nitrate and high relative humidity related secondary aerosol, and resuspended dust and diesel vehicles (exhaust and non-exhaust) are the top two contributors to pseudo-ultrafine (<0.43 μm), fine (0.43–2.1 μm) and coarse mode (>2.1 μm) PM, respectively. Mass concentration of PM from coal and biomass combustion, industrial emissions, and diesel vehicle sources showed a bimodal size distribution, but gasoline vehicles and resuspended dust exhibited a peak in the fine and coarse mode, separately. Mass concentration of sulphate, nitrate and secondary organic aerosol exhibited a bimodal distribution and were correlated with temperature, indicating strong photochemical processing and repartitioning. High relative humidity related secondary aerosol was strongly associated with size shifts of PM, NO₃⁻ and SO₄²⁻ from the usual 0.43–0.65 μm to 1.1–2.1 μm. Our results demonstrated the dominance of primary combustion sources in the <0.43 μm particle mass, in contrast to that of secondary aerosol in fine particle mass, and dust in coarse particle mass in the Northern China megacity.

A comprehensive modelling approach has been developed to predict population exposure to the ambient air PM₂.₅ concentrations in different microenvironments in London. The modelling approach integrates air pollution dispersion and exposure assessment, including treatment of the locations and time activity of the population in three microenvironments, namely, residential, work and transport, based on national demographic information. The approach also includes differences between urban centre and suburban areas of London by taking account of the population movements and the infiltration of PM₂.₅ from outdoor to indoor. The approach is tested comprehensively by modelling ambient air concentrations of PM₂.₅ at street scale for the year 2008, including both regional and urban contributions. Model analysis of the exposure in the three microenvironments shows that most of the total exposure, 85%, occurred at home and work microenvironments and 15% in the transport microenvironment. However, the annual population weighted mean (PWM) concentrations of PM₂.₅ for London in transport microenvironments were almost twice as high (corresponding to 13–20 μg/m³) as those for home and work environments (7–12 μg/m³). Analysis has shown that the PWM PM₂.₅ concentrations in central London were almost 20% higher than in the surrounding suburban areas. Moreover, the population exposure in the central London per unit area was almost three times higher than that in suburban regions. The exposure resulting from all activities, including outdoor to indoor infiltration, was about 20% higher, when compared with the corresponding value obtained assuming inside home exposure for all times. The exposure assessment methodology used in this study predicted approximately over one quarter (−28%) lower population exposure, compared with using simply outdoor concentrations at residential locations. An important implication of this study is that for estimating population exposure, one needs to consider the population movements, and the infiltration of pollution from outdoors to indoors.

The determination of the spatiotemporal patterns and driving factors of PM₂.₅ is of great interest to the atmospheric and climate science community, who aim to understand and better control the atmospheric linkage indicators. However, most previous studies have been conducted on pollution-sensitive cities, and there is a lack of large-scale and long-term systematic analyses. In this study, we investigated the spatiotemporal evolution of PM₂.₅ and its influencing factors by using an exploratory spatiotemporal data analysis (ESTDA) technique and spatial econometric model based on remote sensing imagery inversion data of the Yangtze River Economic Belt (YREB), China, between 2000 and 2016. The results showed that 1) the annual value of PM₂.₅ was in the range of 23.49–37.67 μg/m³ with an inverted U-shaped change trend, and the PM₂.₅ distribution presented distinct spatial heterogeneity; 2) there was a strong local spatial dependence and dynamic PM₂.₅ growth process, and the spatial agglomeration of PM₂.₅ exhibited higher path-dependence and spatial locking characteristics; and 3) the endogenous interaction effect of PM₂.₅ was significant, where each 1% increase in the neighbouring PM₂.₅ levels caused the local PM₂.₅ to increase by at least 0.4%. Natural and anthropogenic factors directly and indirectly influenced the PM₂.₅ levels. Our results provide spatial decision references for coordinated trans-regional air pollution governance as well as support for further studies which can inform sustainable development strategies in the YREB.