Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal

Island species are difficult to conserve because they face the synergy of climate change, invasive species, deforestation, and increasing human population densities in areas where land mass is shrinking. The Caribbean island of Hispaniola presents particular challenges because of geopolitical complexities that span 2 countries and hinder coordinated management of species across the island. We employed species distribution modeling to evaluate the impacts of climatic change and anthropogenic activities on the distribution of an endemic mammal of conservation concern, the Hispaniolan solenodon (Solenodon paradoxus). We aggregated occurrence points for this poorly known species for the Last Glacial Maximum (LGM) and the present (1975–2016) based on museum collections, online biodiversity databases, and new field surveys. We quantified degree of overlap between periods and scenarios with Schoener's D. Through a conservation paleobiology lens, we found that over time humans played an increasing role in shaping the distribution of S. paradoxus, thus, providing a foundation for developing conservation strategies on appropriate spatiotemporal scales. Human population density was the single most important predictor of S. paradoxus occurrence. Densities >166 people/km² corresponded to a near-zero probability of occurrence. Models that accounted for climate but not anthropogenic variables falsely identified suitable habitat in Haiti, where on-the-ground surveys confirm habitat is unavailable. Climate-only models also significantly overestimated the potential for habitat connectivity between isolated populations. Our work highlights that alternative fates for S. paradoxus in the Anthropocene exist across the political border between the Dominican Republic and Haiti due to the fundamentally different economic and political realities of each country. Relationships in the fossil record confirm that Hispaniola's sociopolitical boundary is not biologically significant but instead represents one imposed on the island's fauna in the past 500 years by colonial activity. Our approach reveals how a paleontological perspective can contribute to concrete management insights.     

Inhibition, recovery and oxime-induced reactivation of muscle esterases following chlorpyrifos exposure in the earthworm Lumbricus terrestris

Assessment of wildlife exposure to organophosphorus (OP) pesticides generally involves the measurement of cholinesterase (ChE) inhibition, and complementary biomarkers (or related endpoints) are rarely included. Herein, we investigated the time course inhibition and recovery of ChE and carboxylesterase (CE) activities in the earthworm Lumbricus terrestris exposed to chlorpyrifos, and the ability of oximes to reactivate the phosphorylated ChE activity. Results indicated that these esterase activities are a suitable multibiomarker scheme for monitoring OP exposure due to their high sensitivity to OP inhibition and slow recovery to full activity levels following pesticide exposure. Moreover, oximes reactivated the inhibited ChE activity of the earthworms exposed to 12 and 48 mg kg⁻¹ chlorpyrifos during the first week following pesticide exposure. This methodology is useful for providing evidence for OP-mediated ChE inhibition in individuals with a short history of OP exposure (≤1 week); resulting a valuable approach for assessing multiple OP exposure episodes in the field.     

WRF-Chem simulation of East Asian air quality: Sensitivity to temporal and vertical emissions distributions

This study develops fine temporal (seasonal, day-of-week, diurnal) and vertical allocations of anthropogenic emissions for the TRACE-P inventory and evaluates their impacts on the East Asian air quality prediction using WRF-Chem simulations in July 2001 at 30-km grid spacing against available surface measurements from EANET and NEMCC. For NO₂ and SO₂, the diurnal and vertical redistributions of emissions play essential roles, while the day-of-week variation is less important. When all incorporated, WRF-Chem best simulates observations of surface NO₂ and SO₂ concentrations, while using the default emissions produces the worst result. The sensitivity is especially large over major cities and industrial areas, where surface NO₂ and SO₂ concentrations are reduced by respectively 3–7 and 6–12 ppbv when using the scaled emissions. The incorporation of all the three redistributions of emissions simulates surface O₃ concentrations higher by 4–8 ppbv at night and 2–4 ppbv in daytime over broad areas of northern, eastern and central China. To this sensitivity, the diurnal redistribution contributes more than the other two.     

Improved land cover and emission factors for modeling biogenic volatile organic compounds emissions from Hong Kong

This paper describes a study of local biogenic volatile organic compounds (BVOC) emissions from the Hong Kong Special Administrative Region (HKSAR). An improved land cover and emission factor database was developed to estimate Hong Kong emissions using MEGAN, a BVOC emission model developed by Guenther et al. (2006). Field surveys of plant species composition and laboratory measurements of emission factors were combined with other data to improve existing land cover and emission factor data. The BVOC emissions from Hong Kong were calculated for 12 consecutive years from 1995 to 2006. For the year 2006, the total annual BVOC emissions were determined to be 12,400 metric tons or 9.82 × 10⁹ g C (BVOC carbon). Isoprene emission accounts for 72%, monoterpene emissions account for 8%, and other VOCs emissions account for the remaining 20%. As expected, seasonal variation results in a higher emission in the summer and a lower emission in the winter, with emission predominantly in day time. A high emission of isoprene occurs for regions, such as Lowest Forest-NT North, dominated by broadleaf trees. The spatial variation of total BVOC is similar to the isoprene spatial variation due to its high contribution. The year to year variability in emissions due to weather was small over the twelve-year period (?1.4%, 2006 to 1995 trendline), but an increasing trend in the annual variation due to an increase in forest land cover can be observed (+7%, 2006 to 1995 trendline). The results of this study demonstrate the importance of accurate land cover inputs for biogenic emission models and indicate that land cover change should be considered for these models.     

Ambient TSP concentration and dustfall in major cities of China: Spatial distribution and temporal variability

Based on environmental monitoring data in 93 major cities and meteorological records at 398 weather stations in China from 1981 to 2007, total suspended particle (TSP) concentration, the intensity of dustfall, and sand and dust storm frequency (F_d) were analysed. During the past 27 years, the annual average TSP concentration (C_TSP) in 93 cities was 402 μg m^?3. Annual average C_TSP decreased from the north to the south and from inland to the coast areas with a peak value of 628.8 μg m^?3 in Lanzhou. In the 1980s, 1990s and 2000s, annual average C_TSP was 628.7, 319.2, and 250.1 μg m^?3, respectively. Annual average intensity of dustfall (I_d) was 240.5 t km^?2 a^?1, decreased from northern to southern China and from inland to the coast areas with the maximum value of 717.2 t km^?2 a^?1 in Baotou. In the 1980s, 1990s and 2000s, annual average I_d was 334.8, 220.9, 146 t km^?2 a^?1 respectively. Annual average I_d in the Loess Plateau region was commonly higher than 200 t km^?2 a^?1. The annual average F_d decreased from arid regions in northwestern China to humid areas in southeastern China with two sand and sand storm centers existing in Xinjiang Taklamakan Desert and western Inner Mongolia. The annual average F_d in the 1980s, 1990s, 2000s was 16, 8, 6 days respectively, decreased steadily from 18 days in 1981–5 days in 2007. Annual average I_d had a positive linear relation to annual average C_TSP (R² = 0.96). Annual average F_d had a positive relation with annual average C_TSP (R² = 0.97) as well as annual average I_d (R² = 0.94). TSP was the chief pollutant influencing Air Pollution Index (API) in northern China in spring and winter seasons. Sand and dust storm might be a major factor affecting the temporal variability and spatial distribution of TSP and dustfall in China.     

Sea salt concentrations across the European continent

The oceans are a major source for particles that play an important role in many atmospheric processes. In Europe sea salt may contribute significantly to particulate matter concentrations. We have compiled sodium concentration data as a tracer for sea salt for 89 sites in Europe to provide more insight in the distribution of sea salt across Europe. The annual average sea salt concentrations above land were estimated to range between 0.3 and almost 13 μg m^?3. Maximum concentrations are found at the Irish coast. At coastal sites along the Atlantic and North Sea coast concentrations tend to be around 5 μg m^?3. More inland locations up to about 300 km away from the coast tend to show concentrations between 2 and 5 μg m^?3, whereas sites further away from the coast are characterized by lower concentrations. An analysis of the representativity of the data with respect to a long term average showed that the long average is associated with a standard deviation of around 15%. The compilation of observations provides an improved overview of sea salt concentrations in Europe as well as an improved basis for model validation. Verification of the results of the LOTOS-EUROS model learned that the model represents well the spatial variability of the observed sea salt concentrations very well. However, the absolute concentrations are significantly overestimated due to large uncertainties in the emission and dry deposition parameterizations. Using the high explained variability in the gradients across Europe, the bias-corrected modelled distribution serves as a best estimate of the sea salt distribution across Europe for 2005.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Modelling of Materials Policies

This paper discusses the REAP1 model and its application for the analysis of CO₂ reduction and waste management policies for Japanese petrochemicals. The pros and cons of this modelling approach in comparison to other tools is elaborated. This is followed by a discussion of the model code and the modelling results. The results show that CO₂ policies can have significant impacts on waste flows and waste policies can have significant CO₂ benefits. As a consequence both effects must be considered in policy assessment. Pricing instruments are recommended instead of regulations because of the complex physical relations in the materials life cycle that extend beyond sector boundaries. A taxation approach is superior to a subsidy approach because rebound effects can be avoided.     

Application of cryofocusing hydride generation and atomic fluorescence detection for dissolved mercury species determination in natural water samples

The concentration levels of mercury (Hg) species in natural water samples are usually low. Consequently, accurate analysis with low detection limits is still a major problem. In this work, a method was applied for the simultaneous direct determination of dissolved mercury species in water samples by on-line hydride generation (HG), cryogenic trapping (CT), gas chromatography (GC) and detection by atomic fluorescence spectrometry (AFS). The suitability of the method for real samples with different organic matter and chloride contents was evaluated by recovery experiments in synthetic and natural spiked water samples. The HG method was compared with other current available methods for mercury analysis with respect to the different fraction of mercury analysed, i.e. 'reactive', 'reducible' or total. HG derivatization and SnCl2 reduction (with and without previous oxidation with BrCl) were applied to synthetic and natural (spiked and non-spiked) water samples. The influence of chloride and dissolved organic matter concentrations was studied. The results suggest that the HG procedure is suitable for the simultaneous determination of Hg2+ and MeHg+ in surface water samples. Inorganic mercury analysed by HG (i.e. reducible) is close to the total inorganic mercury.