PM2.5 retrieval from space is still challenging due to the elusive relationship between PM2.5 and aerosol optical depth (AOD), which is further complicated by meteorological factors. In this work, we investigated the diurnal cycle of PM2.5 in China, using ground-based PM measurements obtained at 226 sites of China Atmosphere Watch Network during the period of January 2013 to December 2015. Results showed that nearly half of the sites witnessed a PM2.5 maximum in the morning, in contrast to the least frequent occurrence (5%) in the afternoon when strong solar radiation received at the surface results in rapid vertical diffusion of aerosols and thus lower mass concentration. PM2.5 tends to peak equally in the morning and evening in North China Plain (NCP) with an amplitude of nearly twice or three times that in the Pearl River Delta (PRD), whereas the morning PM2.5 peak dominates in Yangtze River Delta (YRD) with a magnitude lying between those of NCP and PRD. The gridded correlation maps reveal varying correlations around each PM2.5 site, depending on the locations and seasons. Concerning the impact of aerosol diurnal variation on the correlation, the averaging schemes of PM2.5 using 3-h, 5-h, and 24-h time windows tend to have larger R biases, compared with the scheme of 1-h time window, indicating diurnal variation of aerosols plays a significant role in the establishment of explicit correlation between PM2.5 and AOD. In addition, high cloud fraction and relative humidity tend to weaken the correlation, regardless of geographical location. Therefore, the impact of meteorology could be one of the most plausible alternatives in explaining the varying R values observed, due to its non-negligible effect on MODIS AOD retrievals. Our findings have implications for PM2.5 remote sensing, as long as the aerosol diurnal cycle, along with meteorology, are explicitly considered in the future.

The study investigated the degradation behaviors of swine farm tetracyclines (TCs) at a catchment scale and explored whether multi-pond systems could be beneficial to the interception of TCs so as to reduce the pollution risk to receiving rivers. The occurrence and migration of 12 kinds of tetracycline antibiotics, including their degradation products, were studied in four swine farms of the Meijiang River basin in China. The migration paths of the TCs were examined through sampling and analyzing the soil and/or sediment at different points along the swine wastewater outlet, which included sewer, sewage pond, mixed-canal (stream and sewage), farmland (paddy and upland soil) and finally the river. TC concentrations of all collected samples were obtained by solid phase extraction followed by measurement with high-performance liquid chromatography tandem mass spectrometry. The results showed that sediment TC concentrations varied greatly in different swine farms, from mg·kg−1 to μg·kg−1 levels. TCs had different decay patterns along different migration paths, such that TCs decayed exponentially in paddy soil, while linearly in sewer and mixed canal. The concentrations of TCs and their degradation products decreased in the order: sewer sediment > sewage pond sediment > mixed-canal sediment > paddy soil > upland soil, indicating that TCs tend to be more easily intercepted and accumulated in water-sediment systems such as ponds. Therefore, the multi-pond system could be an effective way to prevent TCs from migrating into rivers. These results provided essential information for contamination control of antibiotics in aquatic environments.

An Aerodyne quadrupole aerosol mass spectrometry (Q-AMS) was utilized to measure the size-resolved chemical composition of non-refractory submicron particles (NR-PM1) from October 27 to December 3, 2014 at an urban site in Lanzhou, northwest China. The average NR-PM1 mass concentration was 37.3 μg m−3 (ranging from 2.9 to 128.2 μg m−3) under an AMS collection efficiency of unity and was composed of organics (48.4%), sulfate (17.8%), nitrate (14.6%), ammonium (13.7%), and chloride (5.7%). Positive matrix factorization (PMF) with the multi-linear engine (ME-2) solver identified six organic aerosol (OA) factors, including hydrocarbon-like OA (HOA), coal combustion OA (CCOA), cooking-related OA (COA), biomass burning OA (BBOA) and two oxygenated OA (OOA1 and OOA2), which accounted for 8.5%, 20.2%, 18.6%, 12.4%, 17.8% and 22.5% of the total organics mass on average, respectively. Primary emissions were the major sources of fine particulate matter (PM) and played an important role in causing high chemically resolved PM pollution during wintertime in Lanzhou. Back trajectory analysis indicated that the long-range regional transport air mass from the westerly was the key factor that led to severe submicron aerosol pollution during wintertime in Lanzhou.

To gain a better understanding of the impacts from potential risk sources, we developed an oil spill model using probabilistic method, which simulates numerous oil spill trajectories under varying environmental conditions. The statistical results were quantified from hypothetical oil spills under multiple scenarios, including area affected probability, mean oil slick thickness, and duration of water surface exposed to floating oil. The three sub-indices together with marine area vulnerability are merged to compute the composite index, characterizing the spatial distribution of risk degree. Integral of the index can be used to identify the overall risk from an emission source. The developed model has been successfully applied in comparison to and selection of an appropriate oil port construction location adjacent to a marine protected area for Phoca largha in China. The results highlight the importance of selection of candidates before project construction, since that risk estimation from two adjacent potential sources may turn out to be significantly different regarding hydrodynamic conditions and eco-environmental sensitivity.

Nonylphenol (NP), ubiquitously detected as the degradation product of nonionic surfactants nonylphenol polyethoxylates, has been reported as an endocrine disrupter. However, most pure microorganisms can degrade only limited species of NP with low degradation efficiencies. To establish a microbial consortium that can effectively degrade different forms of NP, in this study, we isolated a facultative microbial consortium NP-M2 and characterized the biodegradation of NP by it. NP-M2 could degrade 75.61% and 89.75% of 1000 mg/L NP within 48 h and 8 days, respectively; an efficiency higher than that of any other consortium or pure microorganism reported so far. The addition of yeast extract promoted the biodegradation more significantly than that of glucose. Moreover, surface-active compounds secreted into the extracellular environment were hypothesized to promote high-efficiency metabolism of NP. The detoxification of NP by this consortium was determined. The degradation pathway was hypothesized to be initiated by oxidization of the benzene ring, followed by step-wise side-chain biodegradation. The bacterial composition of NP-M2 was determined using 16S rDNA library, and the consortium was found to mainly comprise members of the Sphingomonas, Pseudomonas, Alicycliphilus, and Acidovorax genera, with the former two accounting for 86.86% of the consortium. The high degradation efficiency of NP-M2 indicated that it could be a promising candidate for NP bioremediation in situ.

Northern gannet (Morus bassanus) eggs from Bonaventure Island, Québec, Canada, were collected to monitor concentrations of contaminants. Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDDs/Fs) and non-ortho polychlorinated biphenyls (PCBs) were measured in eggs from 2004 and 2009, and several brominated and nonbrominated flame retardants (FRs) were measured every 2–5 years in eggs from 1994 to 2014. The sum (Σ) concentrations of PCDDs/Fs were significantly lower in 2009 relative to 2004, but the total toxic equivalent concentrations for PCDDs, PCDFs, and PCBs showed no significant differences (196 ng/kg wet weight (ww) in 2004 and 220 ng/kg ww in 2009). The mean ΣFR concentrations decreased significantly between 1994 and 2014, from 58 ng/g ww to 19 ng/g ww. Hexabromocyclododecane (HBCDD) was the principal nonbrominated FR detected in gannet eggs and ranged from <1.0 ng/g ww to 6.9 ng/g ww. The PCDD/F and nonortho PCB profiles were dominated by 2,3,7,8- tetrachloro-dibenzofuran (2,3,7,8-TCDF; from 26.2 ng/g ww to 34.8 ng/kg ww) and PCB-77 (from 1580 ng/g ww to 2650 ng/kg ww), respectively. Although the values of both ecological tracer stable isotopes of carbon (δ13C) and nitrogen (δ15N) showed differences among the years, no temporal trends were observed, which indicates relatively stable adults' diet and foraging area over this time period. The trends over time in concentrations of the studied contaminants likely reflect a decrease in environmental contamination. The mean 2012 eggshell thickness was 10% lower than the pre-DDT value and corresponded to a year of poor reproductive success.

Bisphenol A (BPA), a suspected endocrine disruptor, can modify normal plant growth and development. Photosynthesis provides material and energy for the growth and development of plants, in which chlorophyll (Chl) plays a significant role. Many studies have shown that the growth and metabolism of plants vary at different growth stages. Thus the sensitivity of plant's responses to environmental pollution is correspondingly different. We studied the effects of BPA on the Chl contents of soybean (Glycine Max L.) at different growth stages (seedling, flowering and podding, seed-filling and maturation) by measuring the contents of essential intermediates (5-aminolevulinic acid, porphobilinogen, protoporphyrin IX, magnesium protoporphyrin and protochlorophyll) and the activities of key enzymes (5-aminolaevulinic acid dehydratase, porphobilinogen deaminase, uroporphyrinogen III synthase, magnesium chelatase) in chlorophyll synthesis. Low-dose (1.5 mg/L) BPA exposure increased the activities of key enzymes in addition to the contents of intermediates in Chl synthesis at different growth stages, resulting in increases in Chl contents and net photosynthetic rate. In contrast, medium and high-dose (17.2, 50.0 mg/L) BPA exposure produced inhibitory effects on the indices. Following the withdrawal of BPA exposure, the indices recovered to a degree that was related to the plant growth stage. The effect level (high to low) of BPA on these indices at different growth stages was: seedling stage > maturation stage > flowering and podding stage > seed-filling stage. The reverse effect was observed following the withdrawal of BPA exposure. The responses of key enzymes in plant Chl synthesis to BPA illustrate how BPA affects Chl contents. The effects of BPA show clear differences at different plant growth stages.

High levels of fine particulate matter (PM2.5) are known to cause adverse effects to human health. The goal of this study was to estimate the acute health effects of short-term exposure to ambient PM2.5 by analyzing cause-specific emergency ambulance dispatches as the endpoint in Chengdu, a city in Sichuan Province in southwest China. The ambient PM2.5 concentration of Chengdu reached 63 μg/m3 in 2015. Data related to the causes of specific emergency ambulance dispatches, air pollution, and meteorological conditions were collected from 2013 to 2015 (1095 days). A generalized additive model (GAM) was constructed to control the confounding conditions and to estimate the effects of PM2.5 on human health conditions. Emergency ambulance dispatches for all causes with (RR for lag0 = 1.0010, 95%CI: 1.0002, 1.0019) or without injuries (RR for lag0 = 1.0012, 95%CI: 1.0002, 1.0022), respiratory diseases (RR for lag0 = 1.0051, 95%CI: 1.0012, 1.0089), and cardiovascular diseases (RR for lag0 = 1.0041, 95%CI: 1.0009, 1.0074) were associated with ambient PM2.5 concentrations in Chengdu. In addition, the effects of PM2.5 were not confounded by ozone.

Methane (CH4) and ammonia (NH3) directly and indirectly affect the atmospheric radiative balance with the latter leading to aerosol generation. Both have important spectral features in the Thermal InfraRed (TIR) that can be studied by remote sensing, with NH3 allowing discrimination of husbandry from other CH4 sources. Airborne hyperspectral imagery was collected for the Chino Dairy Complex in the Los Angeles Basin as well as in situ CH4, carbon dioxide (CO2) and NH3 data. TIR data showed good spatial agreement with in situ measurements and showed significant emissions heterogeneity between dairies. Airborne remote sensing mapped plume transport for ∼20 km downwind, documenting topographic effects on plume advection. Repeated multiple gas in situ measurements showed that emissions were persistent on half-year timescales. Inversion of one dairy plume found annual emissions of 4.1 × 10⁵ kg CH4, 2.2 × 10⁵ kg NH3, and 2.3 × 10⁷ kg CO2, suggesting 2300, 4000, and 2100 head of cattle, respectively, and Chino Dairy Complex emissions of 42 Gg CH4 and 8.4 Gg NH3 implying ∼200k cows, ∼30% more than Peischl et al. (2013) estimated for June 2010. Far-field data showed chemical conversion and/or deposition of Chino NH3 occurs within the confines of the Los Angeles Basin on a four to six h timescale, faster than most published rates, and likely from higher Los Angeles oxidant loads. Satellite observations from 2011 to 2014 confirmed that observed in situ transport patterns were representative and suggests much of the Chino Dairy Complex emissions are driven towards eastern Orange County, with a lesser amount transported to Palm Springs, CA. Given interest in mitigating husbandry health impacts from air pollution emissions, this study highlights how satellite observations can be leveraged to understand exposure and how multiple gas in situ emissions studies can inform on best practices given that emissions reduction of one gas could increase those of others.

In recent years, severe pollution events were observed frequently in India especially at its capital, New Delhi. However, limited studies have been conducted to understand the sources to high pollutant concentrations for designing effective control strategies. In this work, source-oriented versions of the Community Multi-scale Air Quality (CMAQ) model with Emissions Database for Global Atmospheric Research (EDGAR) were applied to quantify the contributions of eight source types (energy, industry, residential, on-road, off-road, agriculture, open burning and dust) to fine particulate matter (PM2.5) and its components including primary PM (PPM) and secondary inorganic aerosol (SIA) i.e. sulfate, nitrate and ammonium ions, in Delhi and three surrounding cities, Chandigarh, Lucknow and Jaipur in 2015. PPM mass is dominated by industry and residential activities (>60%). Energy (∼39%) and industry (∼45%) sectors contribute significantly to PPM at south of Delhi, which reach a maximum of 200 μg/m³ during winter. Unlike PPM, SIA concentrations from different sources are more heterogeneous. High SIA concentrations (∼25 μg/m³) at south Delhi and central Uttar Pradesh were mainly attributed to energy, industry and residential sectors. Agriculture is more important for SIA than PPM and contributions of on-road and open burning to SIA are also higher than to PPM. Residential sector contributes highest to total PM2.5 (∼80 μg/m³), followed by industry (∼70 μg/m³) in North India. Energy and agriculture contribute ∼25 μg/m³ and ∼16 μg/m³ to total PM2.5, while SOA contributes <5 μg/m³. In Delhi, industry and residential activities contribute to 80% of total PM2.5.