Ground-level Air Research Articles

Evaluating the use of satellite observations to supplement ground-level air quality data in selected cities in low- and middle-income countries

Using data from ground-level measurements, this work evaluates the performance of one chemical transport model (CTM)-based approach using MERRA2 model output and one statistical approach using a generalized additive model to translate remotely-sensed Aerosol Optical Depth (AOD) measurements from the MODIS combined Deep Blue and Dark Target algorithm to surface-level PM2.5 concentrations for nine cities in low and middle-income countries that include a range of environmental conditions (e.g., mountainous, dusty, or coastal conditions) and only have between 1 and 10 ground level monitoring sites available. This evaluation shows that the CTM-based and statistical approaches tested here generally had a low correlation with the true daily-average PM2.5 values within these nine cities, in contrast to previous studies that had showed stronger correlations over other regions. In addition, the uncertainty in the satellite-based estimates of the daily-average PM2.5 concentration at a given location in a city tended to be very large (21–77% for the statistical methods, and 48–85% for the CTM-based methods). Many cities also had significant limitations in the availability of satellite observations of aerosols throughout the year due to their coastal location, persistent clouds, or persistent seasonal snow cover. The satellite-based methods tested in this work appear to work best for low altitude, inland cities like Hanoi and Delhi, but still have significant errors (43–60%) in predictions of daily-average PM2.5 concentrations at sites within these cities. The CTM-based satellite approach tested here tended to underestimate PM2.5 in high-altitude cities (except for Addis Ababa, Ethiopia, where they overestimate). However, this work suggests that under some conditions, adding satellite data to ground-level monitoring (GLM) network data via co-kriging may reduce the number of GLM sites needed to characterize PM2.5 concentrations within a city, but this needs to be determined on a case-by-case basis. This evaluation is then used to make recommendations to countries with sparse GLM networks on how to incorporate the use of satellite observations in their PM2.5 monitoring and under what conditions satellite approaches are likely to be unsuccessful.

Health impact and related cost of ambient air pollution in Tehran

Ambient air pollution represents one of the biggest environmental risks to health. In this study, we estimated the avoidable mortality burden attributable to ambient air pollution in Tehran, and derived the economic impact associated with these health effects. Using PM2.5 data from ground-level air pollution measurements in Tehran, we estimated PM2.5 exposure for 349 neighborhoods in Tehran, by the Environmental Benefits Mapping and Analysis Program (BenMAP-CE). We considered five scenarios related to PM2.5 levels: an increase to 35 μg/m3; a reduction to 25 μg/m3; a reduction to 15 μg/m3; a reduction to 10 μg/m3 (the WHO's air quality guideline value); and a full roll-back, assuming a reduction to 2.4 μg/m3. All scenarios used 2017 p.m.2.5 levels as a starting point. Using the concentration response function of the Global Exposure Mortality Model (GEMM), we estimated a total of 7146 (95% CI: 6596–7513) adult (age ≥25 years) deaths attributable to PM2.5 in 2017. The leading causes of death were ischemic heart disease (3437; 95% CI: 3315–3516), stroke (886; 95% CI: 693–1002), lower respiratory infections (531: 95% CI: 414–589), chronic obstructive pulmonary disease (364; 95% CI: 271–420), and lung cancer (274; 95% CI: 236–298). The estimated total annual economic benefit (2017) of reducing PM2.5 concentration levels to 2.4 μg/m3 was USD 0.591 (95% CI: 0.447–0.624) billion per year, using the value of a life year (VOLY) approach, and USD 2.894 (95% CI: 2.671–3.043) billion per year, using the value of a statistical life (VSL) approach.

Tropospheric Ozone Formation Estimation in Urban City, Bangi, Using Artificial Neural Network (ANN).

Due to the rapid development of economy and society around the world, the most urban city is experiencing tropospheric ozone or commonly known as ground-level air pollutants. The concentration of air pollutants must be identified as an early precaution step by the local environmental or health agencies. This work aims to apply the artificial neural network (ANN) in estimating the ozone concentration forecast in Bangi. It consists of input variables such as temperature, relative humidity, concentration of nitrogen dioxide, time, UVA and UVB rays obtained from routine monitoring, and data recorded. Ten hidden layer is utilized to obtain the optimized ozone concentration, which is the output layer of the ANN framework. The finding showed that the meteorology condition and emission patterns play an important part in influencing the ozone concentration. However, a single network is sufficient enough to estimate the concentration despite any circumstances. Thus, it can be concluded that ANN is able to give reliable and satisfactory estimations of ozone concentration for the following day.

COMPARATIVE ANALYSIS OF THE CONTRIBUTION OF SHORT-LIVED RADIOIODINES TO THE THYROID RADIATION DOSE FOR THE POPULATION AFTER THE CHERNOBYL AND FUKUSHIMA ACCIDENTS

Purpose. To present results of the comparative analysis of the contribution of short-lived radioiodines to the thyroid radiation dose (TRD) in the population after two severe radiation accidents at nuclear reactors: the Chernobyl accident (1986) and the Fukushima accident (2011). Material and methods. The contribution of short-lived radioiodines to the TRD is expressed in fractions of the TRD from 131I (the main dose forming radionuclide). This contribution takes into account the ratio between doses from inhalation and ingestion intake of 131I, the ratios between dose factors of the expected dose to the thyroid gland in the case of inhalation and ingestion intake of iodine and tellurium isotopes, the ratios between time-integrated concentration of iodine and tellurium isotopes at the ground-level air and in foodstuffs (milk). Results. The typical contribution of short-lived radioiodines to TRD for the population accounts of few percent of dose to the thyroid gland from 131I following the Chernobyl accident as on March 15, 2011, the day of the main fallout after the Fukushima accident - within 15%. For both accidents the leading role among the short-lived radioiodines in terms of dose to the thyroid for the public belongs to 133I and 132I (due to the intake of 132Te and its radioactive decay to 132I in the body). Conclusion. Significant differences in estimates of the typical contribution of short-lived radioiodines to TRD for the population after two considered accidents can be explained by differences in the dominant pathways of the intake of radioiodine by population. The dominant pathway for the vast majority of the population in the contaminated areas following the Chernobyl accident was ingestion intake with locally produced cow’s milk. Following the Fukushima accident the dominant pathway was inhalation intake, because the Japanese authorities were able to quickly prevent the intake of radioiodine with foodstuffs.

Vertical distribution of ozone over Shanghai during late spring: A balloon-borne observation

A tethered balloon-based measurement was conducted to investigate vertical distribution of O3 over Shanghai, China, during May of 2016. The time-series and diurnal variation of ground-level air pollutants (including O3, NO, NO2 and VOCs) were analyzed systematically. By using TrajStat (a GIS-based software), the potential distant contributions of O3 might come from East China Sea, and the Yangtze River Delta (YRD). Within 1000 m above ground, the average vertical profiles of O3 exhibited obviously diurnal characteristics. Most of the NO and O3 profiles measured on high-ozone days demonstrated anti-correlation. The launches on May 11, 2016 revealed that the Atmospheric Boundary Layer (ABL) and shifting of wind direction contributed to the peaks of O3 at the upper altitude. A typical case of vertical mixing of O3 was caught on May 18, 2016, when the ground-level O3 was greatly influenced by the O3 transported from high altitude (1500 m above sea level). The present study provides an important insight of the vertical distribution of O3 over Eastern China, which implied that coupling effects of horizontal and vertical transportations on ground-level ozone should be investigated in future studies.

Some results of determining the source and reasons for the appearance of 106Ru in Russia in September-October 2017

Probable locations of the sources of ruthenium-106 in the atmosphere in September-October 2017 have been considered. Taking into account the monoisotopic nature of the increase in ruthenium-106 concentration in the ground level air and atmospheric precipitation, the most probable version is substantiated, which suggests that ruthenium-106 came from a ground source located in the Southern or the Middle Urals. In order to locate the possible point of Ru-106 emission into the atmosphere, calculations of the time-inversed travel of air masses at the heights of 500-1500 m from the Ru-106 concentration measurement locations at European points during the relevant observation period were used. To confirm the correctness of the source location, calculations were performed that involved simulating regional transport and propagation of radioactivity in the near zone in case of a hypothetical emission of ruthenium-106 from a conventional source in the Southern Urals, in order to compare the simulation results with the available daily ruthenium-106 drop-out measurement data.

Dicarboxylic acids, oxocarboxylic acids and α-dicarbonyls in atmospheric aerosols from Mt. Fuji, Japan: Implication for primary emission versus secondary formation

Aerosol samples were collected at the summit of Mt. Fuji in July–August 2009 and analyzed for diacids and related compounds together with major ions to decipher the sources and formation process of organic aerosols in the free troposphere. Molecular distributions of diacids showed the predominance of oxalic acid (C2) followed by succinic (C4) and malonic (C3) acids. The average concentration of total diacids is ten times higher in whole-day samples than night-only samples due to the uplift of planetary boundary layer in daytime, suggesting the daytime formation of diacids in the uplifted ground-level air mass along the mountain slope. A strong correlation is found between C4 and levoglucosan in whole-day and nighttime samples. Liquid water content (LWC) shows strong correlations in nighttime with anthropogenic and biogenic secondary organic aerosol (SOA) tracers (e.g., adipic (0.90, p < 0.05) and phthalic acids (0.93, p < 0.05) and 3-methyl 2,3,4-trihydroxy-1-butene (0.95, p < 0.05), suggesting that aqueous-phase chemistry is important for the formation of water-soluble organic aerosols in the free troposphere. In whole-day samples, LWC is strongly correlated with organic carbon (r = 0.97, p < 0.05), and isoprene-SOA tracers such as methylthreitol (0.96, p < 0.05), methylerythritol (0.97, p < 0.05), 2-methylglyceric acid (0.94, p <0 .05) and glycolic acid (0.98, p < 0.05), suggesting that daytime SOAs are mainly from the oxidation of isoprene emitted from the regional forests on the foothill of Mt. Fuji. A strong correlation between LWC and glycolic acid further suggests that isoprene is the main precursor for the production of oxalic acid via glycolic acid as intermediate. This study supports the heterogeneous formation of diacids in the free troposphere.

Diurnal cycle of coastal anthropogenic pollutant transport over southern West Africa during the DACCIWA campaign

Abstract. During the monsoon season, pollutants emitted by large coastal cities and biomass burning plumes originating from central Africa have complex transport pathways over southern West Africa (SWA). The Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) field campaign has provided numerous dynamical and chemical measurements in and around the super-site of Savè in Benin (≈185 km away from the coast), which allows quantification of the relative contribution of advected pollutants. Through the combination of in situ ground measurements with aircraft, radio-sounding, satellite, and high-resolution chemistry-transport modeling with the CHIMERE model, the source attribution and transport pathways of pollutants inland (here, NOx and CO) are carefully analyzed for the 1–7 July 2016 period. The relative contributions of different sources (i.e., emissions from several large coastal cities) to the air quality in Savè are characterized. It is shown that a systematic diurnal cycle exists with high surface concentrations of pollutants from 18:00 to 22:00 UTC. This evening peak is attributed to pollution transport from the coastal city of Cotonou (Benin). Numerical model experiments indicate that the anthropogenic pollutants are accumulated during the day close to the coast and transported northward as soon as the daytime convection in the atmospheric boundary layer ceases after 16:00 UTC, reaching 8∘ N at 21:00 UTC. When significant biomass burning pollutants are transported into continental SWA, they are mixed with anthropogenic pollutants along the coast during the day, and this mixture is then transported northward. At night, most of the coastal anthropogenic plumes are transported within the planetary boundary layer (below about 500 m above ground level), whereas the biomass burning pollutants are mostly transported above it, thus generally not impacting ground level air quality.

Simulating lightning NO production in CMAQv5.2: performance evaluations.

This study assesses the impact of the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model on ground-level air quality as well as aloft atmospheric chemistry through detailed evaluation of model predictions of nitrogen oxides (NOx) and ozone (O3) with corresponding observations for the US. For ground-level evaluations, hourly O3 and NOx values from the U.S. EPA Air Quality System (AQS) monitoring network are used to assess the impact of different LNO schemes on model prediction of these species in time and space. Vertical evaluations are performed using ozonesonde and P-3B aircraft measurements during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign conducted in the Baltimore– Washington region during July 2011. The impact on wet deposition of nitrate is assessed using measurements from the National Atmospheric Deposition Program’s National Trends Network (NADP NTN). Compared with the Base model (without LNO), the impact of LNO on surface O3 varies from region to region depending on the Base model conditions. Overall statistics suggest that for regions where surface O3 mixing ratios are already overestimated, the incorporation of additional NO from lightning generally increased model overestimation of mean daily maximum 8 h (DM8HR) O3 by 1–2 ppb. In regions where surface O3 is underestimated by the Base model, LNO can significantly reduce the underestimation and bring model predictions close to observations. Analysis of vertical profiles reveals that LNO can significantly improve the vertical structure of modeled O3 distributions by reducing underestimation aloft and to a lesser degree decreasing overestimation near the surface. Since the Base model underestimates the wet deposition of nitrate in most regions across the modeling domain with the exception of the Pacific Coast, the inclusion of LNO leads to reduction in biases and errors and an increase in correlation coefficients at almost all the NADP NTN sites. Among the three LNO schemes described in Kang et al. (2019), the hNLDN scheme, which is implemented using hourly observed lightning flash data from National Lightning Detection Network (NLDN), performs best for comparisons with ground-level values, vertical profiles, and wet deposition of nitrate; the mNLDN scheme (the monthly NLDN-based scheme) performed slightly better. However, when observed lightning flash data are not available, the linear regression-based parameterization scheme, pNLDN, provides an improved estimate for nitrate wet deposition compared to the base simulation that does not include LNO.

Methods, results and dose consequences of 106Ru detection in the environment in Budapest, Hungary

From late September to early October of 2017, the majority of European networks involved in environmental radiological monitoring – including the environmental monitoring system of the KFKI Campus in Budapest – detected 106Ru isotope of artificial origin in the atmosphere. The reported values higher than the minimum detectable activity (MDA) concentrations were in the range of 0.8 μBq/m3 – 145 mBq/m3. Based on the results of environmental measurements and the available meteorological data, assessments were made to analyze concentration levels of 106Ru activity and to help understand the behavior of radioruthenium in various environmental media. Evaluation of the daily variation of activity levels indicated a maximum of 4 day-long residence time of 106Ru contamination presence in ground level air in Budapest. An average 106Ru activity concentration of 25.6 ± 1.4 mBq/m3 have been observed for the estimated residence time of 106Ru in the air. Deposition of 106Ru was dominantly influenced by rainfall, the major contributor wet deposition which led to an average of 11.3 ± 1.3 Bq/m2 deposition on the ground surface prior to plume passage.

Distribution of greenhouse gases in hyper-arid and arid areas of northern Chile and the contribution of the high altitude wetland microbiome (Salar de Huasco, Chile).

Northern Chile harbors different bioclimatic zones including hyper-arid and arid ecosystems and hotspots of microbial life, such as high altitude wetlands, which may contribute differentially to greenhouse gases (GHG) such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). In this study, we explored ground level GHG distribution and the potential role of a wetland situated at 3800m.a.s.l, and characterized by high solar radiation < 1600Wm-2, extreme temperature ranges (-12 to 24°C) and wind stress (< 17ms-1). The water source of the wetland is mainly groundwater springs, which generates streams and ponds surrounded by peatlands. These sites support a rich microbial aquatic life including diverse bacteria and archaea communities, which transiently form more complex structures, such as microbial mats. In this study, GHG were measured in the water and above ground level air at the wetland site and along an elevation gradient in different bioclimatic areas from arid to hyper-arid zones. The microbiome from the water and sediments was described by high-throughput sequencing 16S rRNA and rDNA genes. The results indicate that GHG at ground level were variable along the elevation gradient potentially associated with different bioclimatic zones, reaching high values at the high Andean steppe and variable but lower values in the Atacama Desert and at the wetland. The water areas of the wetland presented high concentrations of CH4 and CO2, particularly at the spring areas and in air bubbles below microbial mats. The microbial community was rich (> 40 phyla), including archaea and bacteria potentially active in the different matrices studied (water, sediments and mats). Functional microbial groups associated with GHG recycling were detected at low frequency, i.e., < 2.5% of total sequences. Our results indicate that hyper-arid and arid areas of northern Chile are sites of GHG exchange associated with various bioclimatic zones and particularly in aquatic areas of the wetland where this ecosystem could represent a net sink of N2O and a source for CH4 and CO2.

Important Factors for Tornadogenesis as Revealed by High-Resolution Ensemble Forecasts of the Tsukuba Supercell Tornado of 6 May 2012 in Japan

To identify important factors for supercell tornadogenesis, 33-member ensemble forecasts of the supercell tornado that struck the city of Tsukuba, Japan, on 6 May 2012 were conducted using a mesoscale numerical model with a 50-m horizontal grid. Based on the ensemble forecasts, the sources of the rotation of simulated tornadoes and the relationship between tornadogenesis and mesoscale environmental processes near the tornado were analyzed. Circulation analyses of near-surface, tornadolike vortices simulated in several ensemble members showed that the rotation of the tornadoes could be frictionally generated near the surface. However, the mechanisms responsible for generating circulation were only weakly related to the strength of the tornadoes. To identify the mesoscale processes required for tornadogenesis, mesoscale atmospheric conditions and their correlations with the strength of tornadoes were examined. The results showed that two near-tornado mesoscale factors were important for tornadogenesis: strong low-level mesocyclones (LMCs) at about 1 km above ground level and humid air near the surface. Strong LMCs and large water vapor near the surface strengthened the nonlinear dynamic vertical perturbation pressure gradient force and buoyancy, respectively. These upward forces made contributions essential for tornadogenesis via tilting and stretching of vorticity near the surface.

Variability of the Mixed-Layer Height Over Mexico City

The diurnal and seasonal variability of the mixed-layer height in urban areas has implications for ground-level air pollution and the meteorological conditions. Measurements of the backscatter of light pulses with a commercial lidar system were performed for a continuous period of almost six years between 2011 and 2016 in the southern part of Mexico City. The profiles were temporally and vertically smoothed, clouds were filtered out, and the mixed-layer height was determined with an ad hoc treatment of both the filtered and unfiltered profiles. The results are in agreement when compared with values of mixed-layer height reconstructed from, (i) radiosonde data, and (ii) surface and vertical column densities of a trace gas. The daily maxima of the mean mixed-layer height reach values $$> 3\hbox { km}$$ above ground level in the months of March–April, and are clearly lower ( $$< 2.7\hbox { km}$$ ) during the colder months from September–December. Mean daily minima are typically observed at 0700 local time (UTC − 6h), and are lowest during the winter months with values on average below 500 m. The data presented here show an anti-correlation between high-pollution episodes and the height of the mixed layer. The growth rate of the convective mixed-layer height has a seasonal behaviour, which is characterized together with the mixed-layer-height anomalies. A clear residual layer is evident from the backscattered signals recorded in days with specific atmospheric conditions, but also from the cloud-filtered mean diurnal profiles. The occasional presence of a residual layer results in an overestimation of the reported mixed-layer height during the night and early morning hours.

Simulating the mesoscale transport of krypton-85

Due to its half-life, chemical inertness and low solubility in water, radioactive 85Kr is a valuable tracer for testing the performance of atmospheric dispersion models in simulating long-range transport of pollutants. This paper evaluates the capability of simulating the dispersion of radiokrypton emitted by a nuclear fuel reprocessing plant in north-west France. Three time periods during which elevated activity concentrations of 85Kr in ground level air were detected in south-west Germany are chosen. Simulations have been performed using the HYSPLIT code and the European Centre for Median-Range Weather Forecasts (ECMWF) data base. Although their results show a slight trend of underestimating the measured 85Kr concentrations, there is a significant correlation and moderate scatter between observations and simulations with about 50% of the results being within a factor of two of the measured concentrations. The simulated travel time distributions provided a valuable tool for providing additional insight into the dispersion of the tracer radionuclides and for identifying potential causes of deviations between measured and calculated concentrations.

Impacts of trace gaseous emission from fuelwood species on ground level air quality

ABSTRACTNigeria’s energy supply in the form of electricity has been erratic and unreliable in recent time that people now depend on their own power generation in order to meet demands. Thus majority of the populace have to depend on traditional fuelwood for cooking without knowing the impacts of air emissions from it. This study estimated the ground-level concentrations of the air pollutants emitted from the fuelwoods using the American Meteorological Society-Environmental Protection Agency Regulatory Model (AERMOD). The maximum 24 h averaging ground-level concentrations were 6.378–87.319, 1.546–75.164, 0.079–2.759, and 0–0.164 µg/m3, respectively for CO, HC, NO, and SO2. With this all stakeholders will be properly guided on the usage of fuelwood with minimal negative impact.

Reference Point Approach for Multi-objective Assessment and Reduction of Ground-Level O3 Air Quality Monitoring Network in Vojvodina Province, Serbia

A monitoring network of ground-level ozone (O3) concentration levels in Vojvodina Province, Serbia, has been established in several phases, resulting in nine sampling sites (monitoring stations). Because maintenance of a monitoring network is financially very demanding, identifying potentially redundant ozone sites and reducing the network to a cost-effective and functional one are challenging and complex tasks. To provide an easily applicable but reliable analytical framework that will allow decision-makers and other stakeholders to identify redundant ground O3 monitors, the reference point approach, presented by Cetinkaya and Harmancioglu (Journal of Hydrology, 2014), is adopted for a multi-objective assessment of the O3 monitoring network. The evaluation process of the stations’ performance and their ranking is implemented in several phases. Firstly, a comprehensive set of 13 performance attributes is defined and associated with location and environmental criteria, followed by defining the set of alternatives. Next, all required attribute data are collected and stations are evaluated using the reference point approach. Finally, verification of the results is performed by aggregation of ranks obtained using the ideal point multi-criteria methods compromise programing and Technique for Order of Preference by Similarity to Ideal Solution. The aggregation process is performed using the Borda count and Kemeny social choice theory methods. Results indicate that the number of stations can be significantly reduced by 67%. Also, selection of the three best performing stations enabled identification of a core network that is expected to be functionally and financially sustainable under growing environmental and economic pressure.

Unit Commitment Incorporating Spatial Distribution Control of Air Pollutant Dispersion

Air pollution problems are attracting increasing attention, especially among the developing countries with frequent haze events. Renewable energy sources such as wind power are expected to help relieve such environmental concerns. However, air pollution issues under such a changing energy structure receive inadequate attention. Mostly, constraints for total pollutant emissions are considered in unit commitment (UC) and economic dispatch problems. In this paper, we propose a UC model with wind power that considers the dispersion of air pollutants. The dispersion process is described by models involving meteorological conditions and the system's geographical distribution, to estimate the spatial distribution of air pollutants, i.e., the concentration of ground-level air pollutants at monitored locations, such as load centers. A penalty cost is introduced based on this estimation. Particulate matter 2.5 μm or less in diameter, the major air pollutant concerning most developing countries, is selected as the focus of this paper. To properly estimate and sufficiently utilize the benefits of wind power for air pollutant dispersion control, robust optimization is applied to accommodate wind power uncertainty. Case studies justify this consideration of air pollutant dispersion, and demonstrate the effectiveness of the proposed model for improving load centers' air pollution control and utilizing wind power benefits.

Exceptional summer warming leads to contrasting outcomes for methane cycling in small Arctic lakes of Greenland

Abstract. In thermally stratified lakes, the greatest annual methane emissions typically occur during thermal overturn events. In July of 2012, Greenland experienced significant warming that resulted in substantial melting of the Greenland Ice Sheet and enhanced runoff events. This unusual climate phenomenon provided an opportunity to examine the effects of short-term natural heating on lake thermal structure and methane dynamics and compare these observations with those from the following year, when temperatures were normal. Here, we focus on methane concentrations within the water column of five adjacent small lakes on the ice-free margin of southwestern Greenland under open-water and ice-covered conditions from 2012–2014. Enhanced warming of the epilimnion in the lakes under open-water conditions in 2012 led to strong thermal stability and the development of anoxic hypolimnia in each of the lakes. As a result, during open-water conditions, mean dissolved methane concentrations in the water column were significantly (p &lt; 0.0001) greater in 2012 than in 2013. In all of the lakes, mean methane concentrations under ice-covered conditions were significantly (p &lt; 0.0001) greater than under open-water conditions, suggesting spring overturn is currently the largest annual methane flux to the atmosphere. As the climate continues to warm, shorter ice cover durations are expected, which may reduce the winter inventory of methane and lead to a decrease in total methane flux during ice melt. Under open-water conditions, greater heat income and warming of lake surface waters will lead to increased thermal stratification and hypolimnetic anoxia, which will consequently result in increased water column inventories of methane. This stored methane will be susceptible to emissions during fall overturn, which may result in a shift in greatest annual efflux of methane from spring melt to fall overturn. The results of this study suggest that interannual variation in ground-level air temperatures may be the primary driver of changes in methane dynamics because it controls both the duration of ice cover and the strength of thermal stratification.

Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong.

With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with increased and root mean square error values decreased respectively.

Temperature Assessment on a Reclaimed Surface Mine During Northern Bobwhite Breeding Season: Considerations for Habitat Management

Ground-level air temperatures were assessed within 4 distinct habitat areas on a managed reclaimed surface mine at Peabody Wildlife Management Area, Kentucky, 26 June–17 July 2015, during the northern bobwhite (Colinus virginianus) brood season. Habitat consisted of disked and nondisked areas of native grass and an invasive species, sericea lespedeza (Lespedeza cuneata). Disked areas offered more open space for bobwhite mobility and experienced higher average temperatures than nondisked sites. Although statistically significant, differences in air temperature between disked and nondisked areas were likely too small to have practical implications for bobwhite habitat management in Kentucky under current climatic conditions. This will likely change in the future as the regional climate warms and periods of excessive heat are more likely to occur. Consequently, managers may want to consider microclimate when making management decisions.