Baseline Projections Research Articles

On energy and climate change policies: The impact of baseline projections

As a result of statistical contingencies, research frequently employs aged databases to examine the impacts of energy and climate change policies in contemporary situations, or in forward timeframes out to 2050 or even 2100. These forward-looking studies require a base case scenario in order to assess the impacts of a policy. In this article, we hypothesise how a baseline is ‘rolled forward’, and specifically, how this process can materially alter the apparent performance of an energy or climate change policy. In the literature, we find a variety of methods are used to update databases and project forward base case scenarios, some which scale an entire economy to a general trend of growth, whereas others account for sectoral differences. We extend a global electricity-detailed model (GTAP-E-Power) to examine our hypothesis. We evaluate impacts of a world-wide carbon tax policy ($50/t of carbon dioxide equivalent) using three different baselines, with varying levels of specificity relating to macroeconomic projections and sectoral developments and constraints. Results show the impact on sectors and the overall economy in all countries are highly diverse when different baselines are used. For example, fossil-based power output in the United States declines between 36.7 and 65.5% while Real GDP in China declines between −0.66 and −1.54% for an identical policy, depending on which baseline methodology is used. Above all, we find that stronger development of renewable energy and technology in the baselines results in lower costs of a climate change mitigation policy.

Concentration and distribution of lithium in catchment sediments of China: Conclusions from the China Geochemical Baselines project

With the ever-increasing demand for lithium (Li), understanding its concentration and distribution in the pedosphere is essential for alleviating the Li shortage in China. The China Geochemical Baselines (CGB) project, which commenced in 2008, provided comparable global-scale geochemical Li data. A total of 3394 top (0–25 cm) and 3394 deep (below 100 cm) catchment sediment samples were collected. The range of Li concentrations in the top and deep samples were 5.37–400 mg·kg−1 with a median value of 30.0 mg·kg−1, and 5.27–400 mg·kg−1 with a median value of 28.6 mg·kg−1, respectively. The Li concentrations in the top and deep catchment sediments of China showed large variations across regions but only mild variability across profiles. Parent rock, especially granite, predominantly governed the Li distribution in the catchment sediments of China. Landscapes, mineralization and weathering played regional-scale roles. Macroscopically, the low background area (<P25) was mainly distributed in the northern margin of the North China craton, and Hainan Island, and the high background area (>P75) was mainly distributed in the Altay, South China, Sanjiang and Himalayan orogenic belts, and the Yangtze craton. Based on a cumulative frequency of the 85th percentile, a total of 16 geochemical anomalies were identified, and eight important prospective Li resources were selected where many world-renowned Li deposits were formed.

Continental-scale distribution and source identification of fluorine geochemical provinces in drainage catchment sediment and alluvial soil of China

Endemic fluorosis is a worldwide health concern, which may be related to enhanced fluorine (F) in soil via food-to-mouth or respiratory system activity exposure to humans. Until now, continental scale data on F in the pedosphere is still deficient in China. In this paper, the distribution of enhanced F and the factors influencing this distribution are investigated using data of the China Geochemical Baseline project. The median values of F were 488 and 456 ppm in top and deep soil, respectively. In terms of spatial distribution, F in topsoil of China presents coastal and mountain low-value zones, central-south plain and southwest Karst high-value zones, and a northwest arid basin high-value zone. Thirty-three F geochemical provinces were delineated with F values of >700 ppm, which were predominately associated with geological background, intensive evaporation, and human activities. The formation of a high F anomaly area from the central–southern part to the southwestern part of China was related to the calcium-enriched soil and the superimposed coupling of multiple factors including the high F geological background, such as F-enriched organic matter strata, F-enriched phosphorus-bearing strata, F-enriched gypsum salt strata and mineralization processes. The high F anomaly area in northwestern China was not only related to the high geological background, but also associated with the secondary enrichment caused by evaporation.

Emission profile of Pakistan’s agriculture: past trends and future projections

Reducing greenhouse gas (GHG) emissions is a global concern after Paris Agreement (PA). Identification of GHG emission sources and accurate and precise estimation of the corresponding emissions is the first step to meet reduction targets under PA. Increasing share of agricultural emissions in the global concentration has raised concerns on this sector. Now, reducing agricultural emissions without compromising food security is a real challenge. The present study was aimed to provide the current emission profile of Pakistan’s agriculture, historical emission trends and future projections under agricultural growth scenarios according to prescribed guidelines of Intergovernmental Panel on Climate Change (IPCC) for national GHGs inventory development. In this study, GHG emissions were estimated using United Nations Framework Convention on Climate Change (UNFCCC) Non-Annex-I Inventory Software (NAIIS), version 1.3.2 as per prescribed Revised 1996 IPCC Guidelines. In these emission estimations, tier-1 approach (which employs default emission factors) was used in accordance with national circumstances and data availability in the country. The emissions baseline was projected for 2030 under business as usual (BAU), food security (FS) and enhanced consumption pattern (ECP) scenarios. Agriculture sector emitted 174.6 million tons (Mt) of carbon dioxide equivalent (CO2-equivalent) emissions, of which 89.8 Mt is methane (CH4) and 83.7 Mt is nitrous oxide (N2O). Carbon monoxide (CO) emissions were found to be 1.07 Mt of CO2-equivalent. Emission from agricultural soils constituted 45.5% of the total agricultural emissions followed by 45.1% from enteric fermentation and 6.5% from livestock manure management. The rest of 1.7% of the emissions were from rice cultivation followed by 1.1% from burning of crop residue. Historical emission trends showed that the agricultural emissions grew from 71.6 to 174.6 Mt of CO2-equivalent from 1994 to 2015, a 143.8% increase over the period of 21 years. Emissions baseline projections were found to be 271.9, 314.3 and 362.9 Mt tons of CO2-equivalent under BAU, FS and ECP scenarios, respectively.

Basic studies of 3-inch PMT for multi-PMT development

Hyper-Kamiokande is the next generation large-scale water Cherenkov detector. In Hyper-Kamiokade and Intermediate Water Cherenkov Detector for its long baseline project with J-PARC neutrino beam, use of multi-PMT, which is made by combination of 3-inch PMTs, is being considered. As part of multi-PMT development, we measured the characteristics of the 3-inch PMT including the temperature dependence of dark noise rate. The dark noise rate is important characteristic for detection of low energy events including neutron tagging. In addition, since PMT is generally susceptible to the magnetic field, we confirmed the photon detection efficiency in the condition where the magnetic field was applied.

Global Geochemical Baseline Mapping in India for Environmental Management Using Topsoil

Abstract As a part of International Union of Geological Sciences (IUGS)/ International Association of Geochemistry (IAGC) Task Group on Global Geochemical Baselines, CSIR-National Geophysical Research Institute (CSIR-NGRI), Hyderabad, India has carried out geochemical baseline mapping of India to provide high quality data for a wide range of environmental applications. A project based on IUGS global baselines project was initiated by NGRI to cover the whole of India which is having 122 Global Terrestrial Network (GTN)/Global Reference Network (GRNs) of 160 x 160 km. Soil samples were studied in 115 out of the 122 GRN cells in India. 544 topsoil samples were collected for these studies. The soil samples were collected as per the guidelines given in the IUGS/IAGC field manual. The samples were analyzed for 10 major and 12 trace elements (SiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O, TiO2, P2O5, Ba, Co, Cr, Cu, Ni, Pb, Rb, Sr, V, Y, Zn and Zr) by X-ray fluorescence spectrometer at NGRI. The analytical data were computed to prepare geochemical maps showing the distribution of major oxides and trace elements all over India. These maps will help to know the distribution of the toxic and hazardous metals and their relation to human health. These maps also help to see the hot spots for the entire country and in suggesting remedial measures.

Covid – 19: Impact On The Indian Economy

The onset of COVID-19, the global economy is set to undergo a sharp double-dip recession. As many international agencies have already forecasted, the global growth could be -3 per cent in 2020, which is a decline of about 6 percentage points from the baseline projection of positive 3 per cent growth with no pandemic. Such swings in growth forecasts are unprecedented, and this is due to both health scare with lots of deaths and infections and also due to the lockdown of a major part of the global economy. Added to this, the pandemic appears to be more severe in the industrialized economy. While the forecasts for 2021 suggest a sharp rebound, the trends suggest that the world may need to endure this for a longer period than expected. Unlike the global economy, Indian economy was already in a slowdown phase before the pandemic affected and there were expectations that the economy is on a recovery path. But, with the COVID-19 such hopes are not only dented rather down turn turning out to be much deeper. There are various forecasts that suggest a sharper slowdown. Some forecasts even suggest a negative growth, which was not heard in the past five decades. With the lockdown and with increasing infections, the uncertainty in the economy has increased manifolds. There are also discussions about the shape of the recovery – V or U or W. But, in our view, the most probabilistic recovery could see an elongated U shape.

Capturing Key Energy and Emission Trends in CGE Models: Assessment of Status and Remaining Challenges

Limiting global warming in line with the goals in the Paris Agreement will require substantial technological and behavioural transformations. This challenge drives many of the current modelling trends. This article undertakes a review of 17 state-of-the-art recursive-dynamic computable general equilibrium (CGE) models and assesses the key methodologies and applied modules they use for representing sectoral energy and emission characteristics and dynamics. The purpose is to provide technical insight into recent advances in the modelling of current and future energy and abatement technologies and how they can be used to make baseline projections and scenarios 20-80 years ahead. Numerical illustrations are provided. In order to represent likely energy system transitions in the decades to come, modern CGE tools have learned from bottom-up studies. Three different approaches to baseline quantification can be distinguished: (a) exploiting bottom-up model characteristics to endogenize responses of technological investment and utilization, (b) relying on external information sources to feed the exogenous parameters and variables of the model, and (c) linking the model with more technology-rich, partial models to obtain bottom-up- and pathwayconsistent parameters.

The Impact of Dementia and Extremity Injuries on the Plasticity of Long-term Care Demand: An Analysis of Counterfactual Projection Scenarios Based on German Health Insurance Routine Data

Although demand for long-term care (LTC) in Germany is expected to increase over the coming decades, the LTC sector will struggle to provide sufficient capacity. Evaluating the impact of different risk factors on future LTC demand is necessary in order to make informed policy decisions. With regard to LTC need, dementia and lower extremity injuries (LEI) are common risk factors. Both are used to demonstrate their maximum attainable efficacy in mitigating the future increase in overall LTC need, both at home and in nursing homes.We use a multi-state projection model for which the estimation of the underlying transition and mortality rates is based on longitudinal health claims data from AOK, Germany’s largest public health insurance provider, between 2004 and 2010. We project six different scenarios of LTC for ages 75+ in Germany for the period from 2014 to 2044, including counterfactual scenarios that remove the effects of LEI, dementia, or both. Our multi-state projections distinguish between home-based and institutional LTC.Removing the effect of LTC risk factors mitigates the increase in total LTC demand and postpones demand until a later age. Removing dementia markedly shifts future care demand from institutional LTC to LTC at home and even increases demand for LTC at home at older ages beyond the baseline projection due to the dual function of dementia as a risk factor for both LTC demand and mortality. Removing LEI has less of an effect on overall and sectoral LTC demand. Removing both risk factors at the same time results in the greatest impact, which is even more marked than that of both individual scenarios combined, thus indicating a synergistic relationship between dementia and LEI on LTC risk.The type of LTC demand (home-based or institutional) shows considerable plasticity when specific risk factors are removed. We demonstrate the degree to which LTC demand can be affected in favour of LTC at home, using dementia and LEI as examples of potentially modifiable risk factors, and thus show how the efficacy of potential intervention targets for policy-makers can be assessed.This study provides evidence on the degree of plasticity of future long-term care demand at home and in institutions that would hypothetically be attainable when completely removing specific cognitive or physical risk factors of care need (dementia or lower EI). It is based on large-scale health claims data, which contain longitudinal individual level data on morbidity and long-term care status. A close link exists between the cognitive risk factor of dementia and the type of LTC, as its absence shifts care demand to home-based care at older ages. The study also demonstrates the usefulness of counterfactual projections based on health claims data in assessing the hypothetical maximum efficacy of different intervention strategies.

Establishment of GHGs Emission Reduction Evaluation Methodology on Land Use Change of Paddy Field from Rice to Upland Crop Cultivation

This study was conducted to evaluate the effect of GHGs emission reduction with land use change of paddy field. For this we developed the evaluation methodology to calculate the GHGs emission reduction from land. At first, procedure of ETS (emission trading system) methodology on land use change of paddy field was developed. Second, system boundary for each land use was defined. Finally, evaluation methodology on GHGs emission reduction was established. The amounts of GHGs emission reduction on land use change of paddy field was evaluated as difference between baseline emission (BE) and project emission (PE). The system boundary of BE were ① CH4 emission from anaerobic decomposition of organic material in rice field (BECH4), ② N2O emission from N fertilizer application (BEN2O), and ③ CO2 emission from farming machine use (BECO2). Those of PE were ① N2O emission from N fertilizer application (PEN2O) and ② CO2 emission from farming machine use (PECO2). At the evaluation on PE, methan emission was excluded, which was generated usually at anaerobic condition of paddy. Emission amounts of each gas was converted as carbon dioxide with multiplying global warming potential (GWP). Evaluation methodology on GHGs emission reduction on land use change of paddy field. Factor Calculating formula for GHGs emission Baseline Emission (BE) BE = BECH4 + BEN2O + BECO2 ① CH4 emission from anaerobic decomposition of organic material in rice field BECH4 = A × EFCH4 × GWPCH4 ② N2O emission from N fertilizer application BEN2O = A × EFN2O × GWPN2O ③ CO2 emission from farming machine use BECO2 = A × EFCO2 Project Emission (PE) PE = PEN2O + PECO2 ① N2O emission from N fertilizer application PEN2O = A × EFN2O ×GWPN2O ② CO2 emission from farming machine use PECO2 = A ×EFCO2 Emission Reduction (ER) ER = BE ‑ PE GWP : Global Warming Potential, A : cultivation area (ha), EFCH4 : methane emission factor from rice field (kg CH4 ha-1yr-1), EFN2O : nitrous oxide emission factor with N fertilizer application (kg N2O ha-1yr-1), EFCO2 : carbon dioxide emission factor with farming machine use (kg CO2 ha-1yr-1)

Evaluating Potential Sources of Aggregation Bias with a Structural Optimization Model of the U.S. Forest Sector.

Structural economic optimization models of the forestry and land use sectors can be used to develop baseline projections of future forest carbon stocks and annual fluxes, which inform policy dialog and investment in programs that maintain or enhance forest carbon stocks. Such analyses vary in terms of the degree of spatial, temporal, and activity-level aggregation used to represent forest resources, land cover, and markets. While the statistical and econometric modeling communities widely discuss the effects of aggregation bias and have developed correction techniques, there is limited prior research investigating how aggregation bias may affect structural optimization models. This paper explores potential aggregation bias using the Land Use and Resource Allocation model (LURA), a detailed spatial allocation partial equilibrium model of the U.S. forest sector. We ran a series of projections representing alternative aggregation approaches including averaging forest stocks at plot, county, state, and regional levels, across one-, five, or ten-year age classes, and by two or fourteen forest types. We compared the resulting projections of forest carbon stocks and harvesting activities across each aggregation scenario. This allows us to isolate the effect of aggregation on key variables of interest (e.g., GHG emissions and supply costs), while holding all other structural characteristics of the modeling framework constant. We find that age-class and forest type aggregations have the greatest impact on modeling results, with the potential to substantially impact market and greenhouse gas projections. On the other hand, spatial aggregation has a small impact on national carbon stock projections. Importantly, regional results are greatly impacted by different aggregation approaches, with projected regional cumulative carbon stocks differing by more than 25% across scenarios.

A GIS-Based Water Balance Approach Using a LiDAR-Derived DEM Captures Fine-Scale Vegetation Patterns

Topography exerts strong control on microclimate, resulting in distinctive vegetation patterns in areas of moderate to high relief. Using the Thornthwaite approach to account for hydrologic cycle components, a GIS-based Water Balance Toolset is presented as a means to address fine-scale species–site relationships. For each pixel within a study area, the toolset assesses inter-annual variations in moisture demand (governed by temperature and radiation) and availability (precipitation, soil storage). These in turn enable computation of climatic water deficit, the amount by which available moisture fails to meet demand. Summer deficit computed by the model correlates highly with the Standardized Precipitation–Evapotranspiration Index (SPEI) for drought at several sites across the eastern U.S. Yet the strength of the approach is its ability to model fine-scale patterns. For a 25-ha study site in central Indiana, individual tree locations were linked to summer deficit under different historical conditions: using average monthly climatic variables for 1998–2017, and for the drought year of 2012. In addition, future baseline and drought-year projections were modeled based on downscaled GCM data for 2071–2100. Although small deficits are observed under average conditions (historical or future), strong patterns linked to topography emerge during drought years. The modeled moisture patterns capture vegetation distributions described for the region, with beech and maple preferentially occurring in low-deficit settings, and oak and hickory dominating more xeric positions. End-of-century projections suggest severe deficit, which should favor oak and hickory over more mesic species. Pockets of smaller deficit persist on the landscape, but only when a fine-resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Model (DEM) is used; a coarse-resolution DEM masks fine-scale variability and compresses the range of observed values. Identification of mesic habitat microrefugia has important implications for retreating species under altered climate. Using readily available data to evaluate fine-scale patterns of moisture demand and availability, the Water Balance Toolset provides a useful approach to explore species–environment linkages.

ArcFractal: An ArcGIS Add-In for Processing Geoscience Data Using Fractal/Multifractal Models

Fractal and multifractal models, including the concentration-area (C–A) fractal model, spectrum-area (S–A) multifractal model, and local singularity analysis (LSA) method, are widely applied when processing various geoscience datasets. However, there is lack of ArcGIS-based software that contains these popular fractal and multifractal models. Such a situation hinders the popularization and application of fractal and multifractal models. ArcFractal, an easy-to-use ArcGIS add-in for processing geoscience data using fractal and multifractal models, is introduced in this paper. It is developed using C# based on ArcObject for.Net, ArcEngine 10.2, ZedGraph, and Visual Studio 2010. ArcFractal operations require a Windows 7 operating system and ArcGIS Desktop, version 10.2 or higher. The main application of ArcFractal is to determine geochemical threshold/baseline for separating geochemical patterns into anomalous and background components using the C–A, S–A, and LSA techniques. A case study from China Geochemical Baselines Project (CGB) was used to demonstrate the advantage of ArcFractal for processing geochemical exploration data.

What can we learn about effectiveness of carbon reduction policies from interannual variability of fossil fuel CO2 emissions in East Asia?

Although most countries have submitted their Nationally Determined Contributions (NDC), there is a lack of understanding what policies are effective in terms of carbon emission reduction under the announced pledges. We use East Asia as a case study to estimate the importance of national environmental policies in terms of reduction in fossil fuel carbon emissions (FFCO2). We show that the flagship policies of China, Japan, South Korea and Mongolia in the 2010s were generally beneficial in terms of slowing down FFCO2 growth rates. When flagship polices were enacted, annual FFCO2 growth rate has either slowed down by 1% (South Korea), 5% (Mongolia), 8% (China) or even resulted in a decline (Japan) comparing to prior periods. We find that the 12th Five-Year Plan (12th FYP) of China had the strongest footprint in FFCO2 emission dynamics across East Asia in 2010s. The recent slowest rate of FFCO2 growth across East Asia (2011–2015) temporally corresponds to the 12th FYP. This regional pattern of FFCO2 dynamics is driven by decrements in annual growth of FFCO2, coal use and cement production of China (all ˜8% per yer decrease) during the 12th FYP. Using compound periodical growth of FFCO2 emissions, we provide two baseline projections of emission distribution in East Asia, by assuming that all policies are enacted (policy-on) or not (policy-off) in the future. The projections show that policies were beneficial since policy-on scenario results in 24%, 80%, 166% less FFCO2 emissions than in policy-off scenario in East Asia by 2020, 2025 and 2030 respectively. This progress is yet insufficient for reaching NDC goals by 2030. Even in policy-on scenario in 2030, East Asian countries would either experience insufficient decline of FFCO2 like Japan (-13% of FFCO2 comparing to pledged -17%) or increase of FFCO2 like South Korea (11%) and Mongolia (4%) comparing to 2010 level. For China, due to lack of economy-independent goals, we were unable to assess NDC target compliance. We demonstrate that China will remain as the major FFCO2 emitter of EA in near future in any projection. For China, the highest emission cluster will remain at the Eastern Provinces with the strongest power generation demand. These provinces would be responsible for 43% and 52% of FFCO2 emissions in East Asia in policy-off and policy-on scenarios. We concluded that the current efforts of national flagship environmental policies are beneficial but not sufficient for reaching ambitious carbon reduction goals like Paris Agreement. This study once again underlined the necessity in the supranational framework that may control the carbon abatement goals in East Asia. Without the supranational framework, achievements in carbon emission reductions are strongly hindered by the socioeconomic environment and the regional (or sectoral) emphasis of carbon reduction activities within a national economy.

Concentrations, variations and distribution of molybdenum (Mo) in catchment outlet sediments of China: Conclusions from the China geochemical baselines project

The concentrations, variations and distribution of molybdenum (Mo) in catchment outlet sediments from China were studied in this contribution based on the results of recently-finished, continental-scale, China Geochemical Baselines (CGB) project. The data from CGB were combined with other published data-sets with the purpose of understanding the spatial distribution of Mo in China and, in addition, relating the observed geochemical features to natural and/or anthropogenic processes. This geochemical mapping with a density of ca. 3000 km2 per site involves catchment sediments in two horizons at each site: a top sample (TOS) at a depth of 0–25 cm and a bottom sample (BOS) at a depth greater than 100 cm. In total, 3382 TOS and 3380 BOS samples were collected. The analytical results show that the concentrations of Mo in the catchment outlet sediments of China range from 0.07 to 57.86 μg/g for the TOS and 0.09–32.43 μg/g for the BOS. The median and mean values of the TOS data are 0.73 and 1.01 μg/g respectively, and those of the BOS data are 0.71 and 0.94 μg/g. The variations of both the TOS and BOS are high at this continental scale. The Mo concentrations vary greatly from one geological and/or geographic unit to another. For instance, from the Cathaysia Block with the TOS and BOS median values of 1.22 and 1.46 μg/g to the North China craton with those of approximately 0.61 and 0.58 μg/g. Various processes govern the spatial distribution of Mo in the catchment sediments of China but regional-scale natural sources (e.g. lithologies) predominate. Sedimentary sandstones and carbonate rocks, alluvium in plain terrain and aeolian materials (e.g. loess) account for the extensive low concentrations (<0.5 μg/g) at such regions as the Songpan-Ganzi orogen and Songliao Basin; whereas shales, basalts and granitoids like granodiorite, plagiogranite and granite porphyry are taken to be responsible for the high concentrations (>1.2 μg/g) in the Yangtze and Cathaysia blocks. Simultaneously, some local mineralized areas can be also identified at this scale because the sampled sites just happened to fall on sediments derived from mineralized rocks or anthropogenic addition by mining activities. Furthermore, the TOS share the similar patterns with the BOS indicating relatively stable inheritance and no apparent extensive secondary enrichment or depletion in the catchment sediments of China. The CGB demonstrates that a series of baseline levels of Mo are needed at different regions and scales and ultra-low density mapping can still deliver robust geochemical patterns.

US Sheep Industry and the Public Grazing Fee

Since the mid-1940s US sheep inventory has experienced dramatic declines, which has weakened the sheep industry significantly, making it increasingly important to analyze potential policy implications that could affect US sheep inventories in the future. Public grazing lands are often used in sheep production, especially within the western United States. The public grazing fee is, therefore, a cost within the production of sheep. A US sheep model applying capital stock inventory accounting methodology is developed to model both the supply and demand within the joint sheep and wool industries. The model is used to create a baseline projection for the next several years. Various public grazing fee policies are created to demonstrate the effects of the policies on the levels of sheep inventory and sheep and wool production within the country. Results indicate removing the public grazing fee (set at $0/animal unit month) may slow the rate of decline but would not be effective at reversing the declining trend. This suggests reducing the public grazing fee is not a viable policy option to help bring stability to the sheep and wool industries. However, projections indicate raising the grazing fee would have a substantial adverse effect on the industries. Consideration should be given to these results as grazing fee policy is adjusted moving forward.

Continental-scale geochemical survey of lead (Pb) in mainland China's pedosphere: Concentration, spatial distribution and influences

The China Geochemical Baseline (CGB) project (2008–2012) obtained comparable, continental-scale, geochemical data including lead (Pb) concentrations in the pedosphere. Some 3382 topsoil samples were collected at depths of 0–25 cm. Lead concentrations in soil were determined by inductively coupled plasma mass spectrometry (ICP-MS) using 4-acid extraction under strict quality control. The median Pb concentration throughout China was 22.1 mg/kg and varied between 15.6 and 30 mg/kg according to the morphological landscape. There were predominantly low Pb concentrations in northwestern China and much higher concentrations in southeastern China. This is mainly due to differences in climate and landscape, geology (parent rocks) and the presence of mineralization. The arid and semi-arid landforms in northern and northwestern China had low Pb concentrations. High Pb concentrations were most often linked to geology (occurrence of granite) and climate. The most important Pb anomalies occurred in the southern and southwestern parts of China in areas with known polymetallic mineralization. Such anomalies may be further enhanced by mining or smelting activities.

Interpretation of regional-scale distribution of high Hg in soils of karst area in southwest China

The abundance and spatial distribution of mercury in soil samples covering nearly the whole of China ( c . 9 million km 2 ) were obtained by the China Geochemical Baseline (CGB) project from 2008 to 2015. From the data and maps, it was found that the Hg contents both in the top (0–25 cm) and deep soil (below 100 cm or C-horizon) of the karst area in southwestern China are richer than that of any other geographical landscape areas. Median Hg values for this karst area are 113 and 90 µg/kg respectively ( n = 126), in the top and bottom soils, much higher than the corresponding data of 26 and 18 µg/kg for the entire country ( n = 3380). This regional-scale high Hg distribution is due mainly to high Hg geochemical backgrounds in bedrock and soil formation on limestone. A large-scale epithermal metallogenic domain developed in southwestern China and the extensive distribution of Lower Cambrian black shale in southwest China led to a high Hg geochemical background for parent rocks of soils. The chemical weathering of carbonate minerals and the geochemical behaviour of Hg in the epigenetic environment result in Hg enrichment by ferric oxides, iron hydroxide and organic carbon in limestone soils. Human activities mostly result in local-scale Hg anomalies, but have little effect on this regional-scale anomaly.

Potential emission reductions from India’s transport sector: a view from the green transportation projects under CDM

In most populated countries like India, the need for public and private transportation is much more essential as it one of the crucial sectors that helps in the economic growth. On the other hand, it is responsible for emitting greenhouse gases and causes serious air and noise pollutions. This is due to the lack of sustainable principles and activities in the transportation sector. Hence there is a need for sustainability in the transportation sector, and it is very much essential, and the strive for achieving it should be a continuous activity. In this paper, various green transportation projects (GTP) undertaken for reducing the emissions in India’s transport sector were studied. A total of 9 projects were initiated under the clean development mechanism (CDM), contributing to the 760504.69 t CO2 baseline emission reduction, and causing around 275799.2 t CO2 project emissions. However, from these 9 GTP’s 501952.7 t CO2 emissions were reduced. Average values of baseline emission, project emission, and emission reduction from 9 GTP’s were estimated to be around 84500.52 t CO2, 30644.36 t CO2, and 55772.52 t CO2 respectively.

Current and future glacier and lake assessment in the deglaciating Vilcanota-Urubamba basin, Peruvian Andes

Abstract Glacier shrinkage is a strong driver of change for mountain hydrology and landscape development and bears multiple risks as well as new options for human livelihoods. In the tropical Andes, current rates of glacier loss are investigated to some point but associated future extent of both vanishing glacier and forming lake areas and volumes are poorly explored. This study combines an analysis of current (1988–2016) and future (2050/2100) glacier and lake development in the Vilcanota-Urubamba basin (Cusco, Southern Peru). Total glacier area (volume) decreased by 37.3% (20.5%) from 226.1 km2 (8.122 km3) in 1988 to 141.7 km2 (6.457 km3) in 2016. Adjacent lakes increased in area (number) by 15.5% (18.3%) from 23.3 km2 (460 lakes) in 1988 to 26.9 km2 (544 lakes) in 2016 while corresponding lake volume has grown by 9.7% from 0.637 km3 to 0.699 km3, respectively. High spatiotemporal variability can be observed in the basin, with strongest glacier shrinkage in the lower lying northwest (Cordilleras Urubamba and Vilcabamba) and highest growth and lake extent in the Altiplano region of the southeast (Cordillera Vilcanota and Quelccaya ice cap). Future glacier areas could substantially decrease between 40.7% (RCP2.6) and 44.9% (RCP8.5) within the next decades (2031–2060) and between 41.4% and 92.7%, respectively, within this century (2071–2100). Hence, Andean landscapes would transform into mostly glacier-free areas with some remaining ice-covered summits over ~6000 m asl. and this would imply a loss of permanently stored water of several km3. Until the end of this century, important future lake areas could develop and continue to grow between 3.2% (RCP 2.6) and 6.0% (RCP8.5) with an associated volume increase of 0.032 km3 (4.6%) and 0.041 km3 (5.9%), respectively. Our current baseline and future projections suggest that a decrease of glacier shrinkage is also followed by a slowdown in lake formation and particularly volume growth which might have already developed or occur in the near-future. Under the depicted scenarios of change, strong emphasis needs to be promptly put on feasible water management and storage options as robust adaptation measures tackling high uncertainties, risks and complex hydroclimatic and socioenvironmental intertwining.