Km2 Grid Research Articles

Water Level and the Potentials for Wetland Formation and Sustainability in Lower Ogun River Floodplain, Nigeria

Identification, delineation and monitoring of wetlands which requires the understanding and application of their ecological characteristics are critical factors in wetland management and conservation. This study assessed the potentials of wetland formation and sustainability in the lower Ogun river basin by determining the levels of surface and ground water. The study area was divided into 1 km2 grids of 67 units using 0.052 % sampling intensity for the assessments in dry and wet seasons. Monthly water table levels were assessed in 50 cm soil pit while inundation levels were measured during the flooding event using staff gauge. Assessment was carried out for one year during which frequency and periodicity of water table and inundation events were recorded. Results revealed that low water table level ranged from 5 to 45cm of soil depth and occurred between August and September within 6 grids. Water table and surface water was recorded within a period of 2 – 10 weeks during the rainy season. The peak of water levels coincided with the peak of precipitation (> 200 mm) ranging from 30 to 280 cm between September and October while covering 28.75 km2. Conclusively, surface and groundwater levels were recorded during the rainy season having direct variation with the volume of precipitation for a duration that is long enough to support the formation of wetland hydrophytes and hydric soil.
 Keywords: Wetlands; Hydrology; Ground water; Surface water; Inundation; Precipitation

The assessment of soil loss by water erosion in China

Soil erosion is a major environmental problem in China. Planning for soil erosion control requires accurate soil erosion rate and spatial distribution information. The aim of this article is to present the methods and results of the national soil erosion survey of China completed in 2011. A multi-stage, unequal probability, systematic area sampling method was employed. A total of 32,948 sample units, which were either 0.2–3 km2 small catchments or 1 km2 grids, were investigated on site. Soil erosion rates were calculated with the Chinese Soil Loss Equation in 10 m by 10 m grids for each sample unit, along with the area of soil loss exceeding the soil loss tolerance and the proportion of area in excess of soil loss tolerance relative to the total land area of the sample units. Maps were created by using a spatial interpolation method at national, river basin, and provincial scales. Results showed that the calculated average soil erosion rate was 5 t ha−1 yr−1 in China, and was 18.2 t ha−1 yr−1 for sloped, cultivated cropland. Intensive soil erosion occurred on cropland, overgrazing grassland, and sparsely forested land. The proportions of soil loss tolerance exceedance areas of sample units were interpolated through the country in 250 m grids. The national average ratio was 13.5%, which represents the area of land in China that requires the implementation of soil conservation practices. These survey results and the maps provide the basic information for national conservation planning and policymaking.

Species richness and functional diversity of isopod communities vary across an urbanisation gradient, but the direction and strength depend on soil type

Urbanisation involves major changes in environmental conditions such as light, temperature, humidity and noise levels, but the effect of urbanisation on soil conditions and soil biodiversity has received less attention. The reported effects on species richness across a rural to urban landscapes are not unequivocal. Positive, negative and neutral effects have been found, but what is causing this ambiguity in the relationship between species richness and urbanisation is poorly understood. Here we tested whether and how urbanisation affects isopod diversity and whether this depends on habitat soil type. We recorded isopod species presence and soil type in each 1 km2 grid cell in a 500 km2 area in and around the city of Amsterdam, the Netherlands. We analysed the relationship between the number of species and the most important traits (body size and drought- and inundation resistance), the percentage built-up area, and soil type (peat or clay) across a rural-urban landscape gradient. Because many studies find a negative effect of urbanization on biodiversity, we expected a decrease in isopod species richness by increasing amount of built-up area. We found a negative association between isopod species richness and the amount of built-up area across the rural-urban landscape gradient when rural soils contained clay, while for rural soils containing peat the highest species richness was found at intermediate levels of urbanisation. Hence, the relationship between isopod species richness and the level of urbanisation was mediated by soil type. We also found a significant relationship between percentage built-up area and functional traits, irrespective of soil type. Specifically, the percentage built-up area showed a positive correlation with isopod drought resistance as well as body size. These results together demonstrate (1) that soil type variation introduces an important, but often overlooked context-dependency in the effect of urbanisation on biodiversity and (2) that a functional trait approach is an important tool for understanding general effects of environmental change on biodiversity, irrespective of context-dependency.

How Much Can Small-Scale Wind Energy Production Contribute to Energy Supply in Cities? A Case Study of Berlin

In light of the Paris Agreement, many cities have undertaken initiatives to become climate-neutral, making decentralized urban energy production more relevant. This paper addresses the potential of urban wind energy production with small wind turbines, using Berlin as an example. Based on a detailed dataset of all buildings and the hourly wind speed on a 1 km² grid, the potential energy production of each building and Berlin as a whole is assessed. The results show that multiple turbines on suitable buildings are necessary to cover a considerable amount of all households’ energy consumption. Nevertheless, the use of small wind turbines is currently beneficial for individual households to reduce their energy expenditures.

A spatial total nitrogen budget for Great Britain

Understanding nutrient budgets makes it possible to predict where and by how much nutrients are accumulating in the environment. Previous studies have considered this problem for nitrogen (N) but have limited themselves to reactive N species (i.e. excluding N2) or have considered total N (including N2) but have been limited to regional or national scales. In this study the spatially-distributed total nitrogen (N) budget of Great Britain (GB) was estimated at a 1 km2 grid scale. The inputs of N considered were: biological N fixation; atmospheric deposition; food and feed transfer; and inorganic synthetic fertilizer. The outputs of N considered were: atmospheric emission; terrestrial denitrification; fluvial loss from the soil; gaseous emissions from sewage treatment plants; direct sewage flux loss; and groundwater loss. All pathways were considered over a number of years. This study constructed a spatially-differentiated total N budget for GB, which not only includes all major N pathways but also distributes the N budget to various land uses with a 1 km2 spatial resolution. The results showed that both sink and source areas exist across GB, although the majority of 1 km2 grid squares were identified as sources. Based on a mass balance model calculated for 2015, total N exhibited a net flux of a source of −1045 (±244) ktonnes N/year. The spatial N budget across GB ranged from −21 (±3) tonnes N/year to 34 (±5) tonnes N/year, where 66% of grid squares were source areas and 34% were sink areas. Urban and arable land use were predominantly source areas: 97% of total urban land use and 98.5% of total arable land use. 65% of grassland was a sink area. The total amount of N released to the environment by human activity in 2015 was −16.65 kg N/ca/yr.

True Size Matters for Conservation: A Robust Method to Determine the Size of Deep-Sea Coral Reefs Shows They Are Typically Small on Seamounts in the Southwest Pacific Ocean

Protection of vulnerable marine ecosystems (VME) is a critical goal for marine conservation. Yet, in many deep-sea settings, where quantitative data are typically sparse, it is challenging to correctly identify the location and size of VMEs. Here we assess the sensitivity of a method to identify coral reef VMEs based on bottom cover and abundance of the stony coral Solenosmilia variabilis on deep seamounts, using image data from a 2018 large survey off Tasmania, Australia. Whilst there was some detectable influence of varying coral cover and the abundance of live coral heads, the distribution of coral reef VMEs was not substantially shifted by changing these criteria or altering the attributes of a moving window used to spatially aggregate coral patches. Whilst applying stricter criteria for classifying VMEs predictably produced smaller areas of coral reef VME, these differences are not sizeable and were often negligible. A model prediction of the area of suitable habitat for coral reef in the Tasmanian area was much greater than that estimated in this study. Coral reef VMEs formed large contiguous ‘blankets’, mainly on the peaks and flanks of seamounts, but were absent from the continental slope where S. variabilis occurred at low abundance (cover) and/or had no living colonies. The true size of the Tasmanian coral reef VMEs ranged from 0.02 to 1.16 km2; this was relatively large compared to reefs of S. variabilis mapped on New Zealand seamounts, but is small compared to the scales used for regional model predictions of suitable habitat (typically 1 km2 grid cell), much smaller than the smallest units of management interest (100s – 1000s km²). That the method is not overly sensitive to the choice of criteria is highly encouraging in the context of designing spatial conservation measures that are robust, although its broader application, including to other VME indicator taxa, needs to be substantiated by scenario testing in different environments. Importantly, it should encourage uptake by the broader community (e.g. fishing and mining sectors) and forms the basis for better predictive VME models at larger spatial scales and beyond single taxa.

Recycling sustainability of waste paper industry in Beijing City: An analysis based on value chain and GIS model

China established a self-organized and market-driven recycling system, which was dominated by the informal sectors. In recent years, the amount of domestically-recycled waste paper grew slower than expectation in China, which may be resulted from a decline in economic sustainability of current recycling system. For understanding the waste paper recycling system in most cities in China, the economic mechanism remains unclear and the city-level data is extremely insufficient. In this work, an index of recycling sustainability (IRS, benefit divided by cost) is analyzed with a resolution of 1 km2 grid in Beijing City, by adopting value chain and GIS methodology. Five degrees of IRS are defined, from high-degree (IRS > 1.10) to low-degree (IRS < 0.95). Different stakeholders in the informal waste paper recycling system were interviewed to fill the data gap. Results show that: (1) from 2015 to 2018, the informal recycling of waste paper accounted for approximate 80% in Beijing; (2) the number of informal recyclables distribution sites decreased from 27 to 11, and their average distance to the city-center rose from 27.5 km to 40.9 km; (3) in 2015 and 2018, the grids with high-degree IRS accounted for 99.5% and 89.2%, respectively, indicating a sustainable waste paper recycling industry in Beijing; and (4) according to the scenario analysis, if the operating cost rises by 30%, the grids with low-degree IRS accounts for 98.5%, indicating a nontrivial challenges when the recycling cost keeps increasing in the future. Policy recommendations are put forward for a more sustainable paper waste recycling system in China.

Gulf-wide data synthesis for restoration planning: Utility and limitations

Multiple funding mechanisms support restoration across the northern Gulf of Mexico. To maximize environmental, societal, and financial benefits of these investments, best use of available science is needed to inform project prioritization and planning processes. Synthesizing available data across the northern Gulf of Mexico can provide information on potential threats to, and benefits from, projects or suites of projects. To achieve this, subject matter experts from Alabama, Florida, Louisiana, Mississippi and Texas were identified with recommendations from each of the RESTORE Act Centers of Excellence. These experts provided known sources of Gulf-wide data and recommended metrics that would be most informative, resulting in 40 threat, 19 habitat and 10 community primary data layers. Two tessellated geospatial hexagon grids were generated to provide uniform coverage that encompassed a 25-mile buffer of the Coastal Zone Management Act (CZMA) boundary at a spatial grid resolution of 100 km2 and 1 km2. The two resultant grid domains included all counties in the five Gulf states determined by the National Oceanic and Atmospheric Administration (NOAA) as contributing to coastal watersheds. The varying grid resolutions allowed for data to be spatially visualized both at a broad Gulf-wide scale on the 100 km2 grid as well as at a regional and project level scale on the 1 km2 grid. The data layers were synthesized into combined layers of potential stress, potential ecological benefits, and potential community benefits. These layers support broad scale prioritization for restoration efforts, based on likelihood of success and desired outcomes. The synthesized data were discussed in the context of the five goals and four priority criteria of the Gulf Coast Ecosystem Restoration Council’s (RESTORE Council) aim of using best available science (BAS) to guide future funding for restoration at large and small scales.

Factors influencing the precision of species richness estimation in Japanese vascular plants

AbstractAimEstimating species richness from a series of samples is an important and widely debated issue in ecology and biodiversity conservation. Numerous tests of respective richness estimators gave insights into the precision, the limitations and the pitfalls of richness forecasting. However, few benchmark tests used almost complete empiric census data obtained at those spatial scales where richness estimation is most useful for conservation management.LocationJapan.MethodsWe use an extraordinary dataset on the spatial distribution of Japanese plants containing complete information on the occurrence of each Japanese plant species at the 10 × 10 km2 grid cell level. We link the estimates of four estimators representing different theoretical approaches, Chao2, rarefaction, species–area relationships (SAR) and species abundance distributions (SAD), to environmental data using a fully nested sampling design.ResultsChao2 and rarefaction behaved very similar in all tests and significantly underestimated true richness below 40% sampling fraction. SAR and SAD were less precise than Chao2 and rarefaction at higher sampling fraction but also less affected by low sample size. In general, SAD provided robust estimates over the whole range of sampling fraction and 67.4% of estimates ranged within the 10% error level. Higher species spatial turnover increased and high evenness in occurrence decreased the precision of the SAD estimator. Precision of the four estimators was largely unaffected by environmental variability but increased with increasing latitude.Main conclusionsOur results strongly indicate that the pattern of Japanese plant species spatial distribution is sufficiently scale invariant for richness estimators to provide precise forecasting results at the country level. The simplest process to generate such a spatial distribution is ecological drift.

Higher rates of liana regeneration after canopy fall drives species abundance patterns in central Amazonia

Abstract In tropical rainforest, most vascular plants have some capacity to resprout, and lianas are often effective resprouters after canopy fall. However, the diversity of resprouting responses of liana species and the consequence for plant persistence are poorly understood. We hypothesized that variation in regeneration among liana species causes differences in liana species abundance in tropical rainforest through differential resprouting capacity, such that liana species with higher densities produce more resprouts after canopy falls. We applied a manipulative field experiment investigating the effect of different levels of disturbance on the production of resprouts and adventitious roots in 10 liana species of the tribe Bignonieae (Bignoniaceae) with contrasting abundances in central Amazonia. We selected 15 individuals of each species and assigned the lianas to three distinct conditions: (a) total canopy fall with lianas severely damaged and detached from trees; (b) partial fall of lianas, without visible damage; and (c) intact lianas (control). We tested whether liana species regeneration patterns were related to species density. Liana species density was calculated using previous research on liana species distribution in 30 1‐ha plots systematically distributed in a 6 × 6 km2 grid at the Ducke Reserve. The number of aerial resprouts produced by lianas under the total canopy fall treatment was twice that of plants under lower levels of disturbance, while the production of adventitious roots did not differ among treatments. Liana species showed different intensities of resprouting, and species with higher average densities on the forest landscape had more resprouts after the total canopy fall treatment. Synthesis. Our results shed new light on the factors that influence liana species abundance, highlighting the role of resprouting after canopy fall and its variation among liana species. Resprouting mitigates the negative effects of canopy damage, suggesting that the impact of increased tree fall disturbances over time, which has been attributed to Amazonian forests in the literature, may increase already abundant liana species with effective resprouting capacity. We identify liana species that are more resilient to disturbance and may alter forest dynamics during climatic change.

New record on Asiatic Golden Cat Catopuma temminckii Vigors &amp; Horsfield, 1827 (Mammalia: Carnivora: Felidae): photographic evidence of its westernmost distribution in Gaurishankar Conservation Area, Nepal

The Asiatic Golden Cat Catopuma temminckii is poorly known in Nepal and was previously recorded only twice in the eastern part of the country. We conducted a camera trap survey in the Lapchi Valley (32km2) of Gaurishankar Conservation Area (GCA), a protected area in north-central Nepal, from October 2018 to April 2019. Eleven cameras were deployed to record mammalian diversity in a 2×2 km2 grid across Lapchi block of GCA. During the study period, four photos and three videos (each of 10 seconds length) of Asiatic Golden Cats were recorded at an elevation of 2,540m at a single camera trap station. This is the first photographic record of Asiatic Golden Cat in this region of Nepal extending the distribution of the species further west in the Himalaya. A more detailed study on its distribution, population size and behaviour is warranted in the near future to implement appropriate conservation measures.&#x0D;

A multi-resolution air temperature model for France from MODIS and Landsat thermal data

Understanding and managing the health effects of ambient temperature (Ta) in a warming, urbanizing world requires spatially- and temporally-resolved Ta at high resolutions. This is challenging in a large area like France which includes highly variable topography, rural areas with few weather stations, and heterogeneous urban areas where Ta can vary at fine spatial scales. We have modeled daily Ta from 2000 to 2016 at a base resolution of 1 km2 across continental France and at a 200 × 200 m2 resolution over large urban areas. For each day we predict three Ta measures: minimum (Tmin), mean (Tmean), and maximum (Tmax). We start by using linear mixed models to calibrate daily Ta observations from weather stations with remotely sensed MODIS land surface temperature (LST) and other spatial predictors (e.g. NDVI, elevation) on a 1 km2 grid. We fill gaps where LST is missing (e.g. due to cloud cover) with additional mixed models that capture the relationship between predicted Ta at each location and observed Ta at nearby weather stations. The resulting 1 km Ta models perform very well, with ten-fold cross-validated R2 of 0.92, 0.97, and 0.95, mean absolute error (MAE) of 1.4 °C, 0.9 °C, and 1.4 °C, and root mean square error (RMSE) of 1.9 °C, 1.3 °C, and 1.8 °C (Tmin, Tmean, and Tmax, respectively) for the initial calibration stage. To increase the spatial resolution over large urban areas, we train random forest and extreme gradient boosting models to predict the residuals (R) of the 1 km Ta predictions on a 200 × 200 m2 grid. In this stage we replace MODIS LST and NDVI with composited top-of-atmosphere brightness temperature and NDVI from the Landsat 5, 7, and 8 satellites. We use a generalized additive model to ensemble the random forest and extreme gradient boosting predictions with weights that vary spatially and by the magnitude of the predicted residual. The 200 m models also perform well, with ten-fold cross-validated R2 of 0.79, 0.79, and 0.85, MAE of 0.4, 0.3, and 0.3, and RMSE of 0.6, 0.4, and 0.5 (Rmin, Rmean, and Rmax, respectively). Our model will reduce bias in epidemiological studies in France by improving Ta exposure assessment in both urban and rural areas, and our methodology demonstrates that MODIS and Landsat thermal data can be used to generate gap-free timeseries of daily minimum, maximum, and mean Ta at a 200 × 200 m2 spatial resolution.

Scale and landscape features matter for understanding the performance of large payments for ecosystem services

Various payment for ecosystem services (PES) programmes are becoming very common across the globe due to ever-strengthening conservation policies and aspirations for socio-ecological sustainability. Nevertheless, quantifying the performance of PES at large spatial scales remains very challenging. Here, a biophysically-based indicator approach is formulated to assess the effectiveness of a new large-scale PES program in China. Structural equation modelling was also used to reveal the possible landscape features that might impact the effectiveness of the PES. The results suggested the overall effectiveness of the PES implementation, but the effectiveness suggested by the analysis tended to decrease with increasingly fine spatial scales from the whole PES implementing region down to 100 km2 grids. The selected landscape features combined to explain 27% of the variability in the effectiveness of the PES programme. The spatial scale and landscape dependency of the effectiveness of PES could provide new insight to support the planning and adaptive management of large PES programmes.

Magnetotelluric multiscale 3-D inversion reveals crustal and upper mantle structure beneath the Hangai and Gobi-Altai region in Mongolia

SUMMARY Central Mongolia is a prominent region of intracontinental surface deformation and intraplate volcanism. To study these processes, which are poorly understood, we collected magnetotelluric (MT) data in the Hangai and Gobi-Altai region in central Mongolia and derived the first 3-D resistivity model of the crustal and upper mantle structure in this region. The geological and tectonic history of this region is complex, resulting in features over a wide range of spatial scales, which that are coupled through a variety of geodynamic processes. Many Earth properties that are critical for the understanding of these processes, such as temperature as well as fluid and melt properties, affect the electrical conductivity in the subsurface. 3-D imaging using MT can resolve the distribution of electrical conductivity within the Earth at scales ranging from tens of metres to hundreds of kilometres, thereby providing constraints on possible geodynamic scenarios. We present an approach to survey design, data acquisition, and inversion that aims to bridge various spatial scales while keeping the required field work and computational cost of the subsequent 3-D inversion feasible. MT transfer functions were estimated for a 650 × 400 km2 grid, which included measurements on an array with regular 50 × 50 km2 spacing and along several profiles with a denser 5–15 km spacing. The use of telluric-only data loggers on these profiles allowed for an efficient data acquisition with a high spatial resolution. A 3-D finite element forward modelling and inversion code was used to obtain the resistivity model. Locally refined unstructured hexahedral meshes allow for a multiscale model parametrization and accurate topography representation. The inversion process was carried out over four stages, whereby the result from each stage was used as input for the following stage that included a finer model parametrization and/or additional data (i.e. more stations, wider frequency range). The final model reveals a detailed resistivity structure and fits the observed data well, across all periods and site locations, offering new insights into the subsurface structure of central Mongolia. A prominent feature is a large low-resistivity zone detected in the upper mantle. This feature suggests a non-uniform lithosphere-asthenosphere boundary that contains localized upwellings that shallow to a depth of 70 km, consistent with previous studies. The 3-D model reveals the complex geometry of the feature, which appears rooted below the Eastern Hangai Dome with a second smaller feature slightly south of the Hangai Dome. Within the highly resistive upper crust, several conductive anomalies are observed. These may be explained by late Cenozoic volcanic zones and modern geothermal areas, which appear linked to mantle structures, as well as by major fault systems, which mark terrane boundaries and mineralized zones. Well resolved, heterogeneous low-resistivity zones that permeate the lower crust may be explained by fluid-rich domains.

Estimation of Travel Climate Comfort Degree in the Cross-border Region between China and Russia Based on GIS

The duration of travel climate comfort degree is an important factor that influences the length of the tourism season and the development of a tourism destination. In this study, we used the monthly average meteorological data for the last 10 years from 46 weather stations in Heilongjiang Province (China) and Primorsky Krai (Russia) to calculate the temperature–humidity index (THI) and wind chill index (WCI) based on ArcGIS software interpolation technology. We obtained the climate comfort charts of the study area with a grid size a 1 km2 grid size, and analyzed the spatial distribution of comfort for each month. The results show the following: 1) The THI and WCI of the cross-border region gradually decrease from south to north and from low altitude to high altitude. The annual comfortable climate period is longer when analyzed in terms of the WCI rather \than the THI. 2) The travel climate comfortable period of the study area shows significant regional difference and the length of the comfortable period in Heilongjiang Province is 4 to 5 months. Meanwhile, the period in Primorsky Krai decreases from south to north and the length of the comfortable period length in its southern region can reach 7 months. 3) The predominant length of the climate comfortable period in the cross-border area is 5 months per year, and it covers 46.6% of the total area, while areas that have a climate comfortable period of 2 months are the most limited, covering less than 0.3% of the area. The results provide a scientific basis for the utilization and development of a meteorological tourism resources and touring arrangements for tourists in the cross-border region between China and Russia.

Estimación de la abundancia de la cabra montés en un hábitat forestal de montaña de gran superficie

El objetivo del estudio fue estimar la distribución y densidad de la cabra montés en la provincial de Castellón, España. Pedimos a los agentes medioambientales del Departamento de Medio Ambiente de la Generalitat de Valencia que estimaran su distribución utilizando cuadrículas de 2,5 x 2,5 km2 e identificaran 130 puntos de observación fijos con buena visibilidad en toda el área. El seguimiento se hizo en dos periodos: junio y julio, tras los partos y noviembre-diciembre, durante el celo. El conteo se realizó tras el amanecer o antes del atardecer durante periodos de 3 horas y para calcular la densidad utilizamos el procedimiento Distance Sampling (DS). Detectamos 1.157 cabras en el 77% de los puntos fijos tras los partos y 1.994 en el 82% de los puntos durante el celo. En el celo la densidad fue de 11,7 cabras km-2 (ICM 95% = 8,9-15,4). El 15% de los machos resultó ser mayor de 10 años, la proporción de sexos en la edad adulta de 0,98 machos por hembra, la productividad 0,75 cabritos por hembra adulta y el tamaño mínimo poblacional de 24.030 individuos. En terrenos forestales rugosos, el procedimiento del DS produce resultados razonables que apoyan su uso para estimar tamaños poblacionales de cabras monteses en estos ambientes de visibilidad reducida.

Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign

Recirculation of pollutants due to a bay breeze effect is a key meteorological mechanism impacting air quality near urban coastal areas, but regional and global chemical transport models have historically struggled to capture this phenomenon. We present a case study of a high ozone (O3) episode observed over the Chesapeake Bay during the NASA Ozone Water-Land Environmental Transition Study (OWLETS) in summer 2017. OWLETS included a complementary suite of ground-based and airborne observations, with which we characterize the meteorological and chemical context of this event and develop a framework to evaluate model performance. Two publicly-available NASA global high-resolution coupled chemistry-meteorology models (CCMMs) are investigated: GEOS-CF and MERRA2-GMI. The GEOS-CF R2 value for comparisons between the NASA Sherpa C-23 aircraft measurements to the GEOS-CF resulted in good agreement (R2: 0.67) on July 19th and fair agreement (R2: 0.55) for July 20th. Compared to surface observations, we find the GEOS-CF product with a 25 × 25 km2 grid box, at an hourly (R2: 0.62 to 0.87) and 15-min (R2: 0.64 to 0.87) interval for six regional sites outperforms the hourly nominally 50 × 50 km2 gridded MERRA2-GMI (R2: 0.53 to 0.76) for four of the six sites, suggesting it is better capable of simulating complex chemical and meteorological features associated with ozone transport within the Chesapeake Bay airshed. When the GEOS-CF product was compared to the TOLNet LiDAR observations at both NASA Langley Research Center (LaRC) and the Chesapeake Bay Bridge Tunnel (CBBT), the median differences at LaRC were −6 to 8% and at CBBT were ±7% between 400 and 2000 m ASL. This indicates that, for this case study, the GEOS-CF is able to simulate surface level ozone diurnal cycles and vertical ozone profiles at small scales between the surface level and 2000 m ASL. Evaluating global chemical model simulations at sub-regional scales will help air quality scientists understand the complex processes occurring at small spatial and temporal scales within complex surface terrain changes, simulating nighttime chemistry and deposition, and the potential to use global chemical transport simulations in support of regional and sub-regional field campaigns.

Burden of disease due to nitrogen dioxide exposure in Germany

Abstract Background Numerous studies identified adverse effects of air pollution on health. According to the recent Global Burden of Disease Study about 2.9 million people died prematurely due to the effects of ambient particulate matter (PM) pollution in 2016, which resulted in about 70 million years of life lost (YLL). In addition to PM, a growing body of evidence shows convincing associations between nitrogen dioxide (NO2) with several health outcomes. The case study provides a health risk assessment for NO2 in Germany. Methods A systematic review was performed to select health outcomes with strong evidence for an association with NO2 and to derive an updated exposure-response function (ERF). The exposure assessment was performed on a 1x1 km2 grid by combining measured and modelled data (annual means of NO2 background concentration) with population density. Exposure data and the ERF were combined by the population attributable fraction formula. The main analysis was performed using a counterfactual of 10 µg/m3. Results Only for cardiovascular mortality the evidence for the association with long-term NO2-exposure was rated as “strong”. Thus, the main analysis merely included this outcome. For the year 2014, 5,966 (95% CI: 2,031-9,893) attributable deaths and 49,726 (95% CI: 16,929-82,456) YLL were estimated. Looking at time trends a decrease of disease burden was observed compared to the year 2007 where 7,832 (95% CI: 2,669-12,973) attributable deaths and 69.244 (95% CI: 23.601-114.690) YLL due to NO2 were calculated. Conclusions Our results show a considerable burden due to NO2 in Germany. Compared to previous estimates for PM (ca. 41,100 attributable deaths in 2014) the burden due to NO2 is much lower. However, due to methodological constraints we could not incorporate higher concentrations from traffic hotspots. This, and the fact that we only considered one health outcome in our main analysis, suggests that our results might be an underestimation.

Impact of Selected Options in the Weather Research and Forecasting Model on Surface Wind Hindcasts in Coastal Ghana

This paper examines the impacts of five planetary boundary layer (PBL) parameterization schemes paired with several compatible surface layer (SL) parameterization schemes in the Weather Research and Forecasting Model on wind hindcasts for resource assessment purposes in a part of Coastal Ghana. Model predictions of hourly wind speeds at 3 × 3 km2 and 9 × 9 km2 grid boxes were compared with measurements at 40 m, 50 m, and 60 m. It was found that the Mellor-Yamada Nakanishi and Niino Level 3 (MYNN3) PBL scheme generally predicted winds with a relatively better combination of error metrics, irrespective of the SL scheme it was paired with. When paired with the Eta surface layer scheme, it often produced some of the relatively fewest errors in estimated mean wind power density (WPD) and Weibull cumulative density. A change in the simulation grid size did not have a significant impact on the conclusions of the relative performance of the PBL-SL pairs that were tested. The results indicate that the MYNN3 PBL and Eta SL pair is probably best for wind speed and energy assessments for this part of coastal Ghana.

Potential efficiency gains in payment programs from resolving spatial and temporal heterogeneity in the cost of supplying forest carbon

The environmental benefits and costs of conservation policies often vary over space and through time. Accounting for this spatial and temporal heterogeneity has important implications for the potential cost effectiveness of different payment program designs. In this study, we examine the cost efficiency gain from spatial and temporal targeting in payment designs for forest carbon storage in the Central and Southern Appalachian Mountains in the Eastern United States. We run a forest land change model and a carbon simulation model utilizing a panel data on forest land and its competing uses, economic returns, and spatial characteristics for each 1 km2 grid cells in 1992, 2001, 2006 and 2011. A time- and space-specific carbon cost for each individual 1 km2 grid cell is calculated that captures the spatial and temporal heterogeneity in carbon cost efficiency. From there, we compare carbon cost efficiency levels of various payment designs that allow for different degrees of spatial and temporal flexibility. We find that 1) spatial targeting improves carbon cost efficiency, and this efficiency gain is larger as payments become more narrowly targeted, 2) this carbon efficiency gain is present in all market conditions, but is largest in a moderately growing market and smallest in a downturn market, 3) accounting for temporal heterogeneity results in even larger carbon efficiency gains, almost double those from spatial targeting. Just as policies that enable spatial targeting (e.g., auctions) increase cost efficiency savings, so too will policy mechanisms that emphasize budget flexibility through time. These could include utilizing loans or flexible conservation financing, or allowing movement across budgeting categories within a given time period.