Environmental Assessment & Climate Change

Expert services can be provided to assist with Environmental Assessments, Compliance with Remedial Targets, and Climate Change. This includes:

Field Investigations, Laboratory Analyses and Monitoring: Sampling to identify and delimitate sources of contamination, field investigations to characterise the extent of soil and groundwater contamination, laboratory tests to determine the properties of the soil, aquifer and contaminant, and monitoring to ensure contaminant concentrations meet acceptable levels.

Soil and Groundwater Risk and Vulnerability Assessments: Risk and vulnerability analyses of soil and groundwater, to ensure compliance with Environment Agency standards, can be assessed using a variety of techniques including: the UK’s Level 1 to 4 procedures; numerical and analytic groundwater models; and, ArcGIS Overlay and Index methods.

The latter includes a whole raft of different models, all founded on the US Environment Protection Agency’s (EPA) DRASTIC Model (1987). This model comprises the  superposition of maps  detailing the depth to water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone and hydraulic conductivity of the aquifer (the acronym DRASTIC). These hydrogeologic factors are used to infer the potential for contaminants to enter ground water. The relative ranking scheme uses a combination of weights and ratings to produce a numerical value, called the DRASTIC INDEX, which helps prioritize areas with respect to ground water contamination vulnerability.

Newer Overlay and Index models tweak, remove or add DRASTIC parameters to investigate contamination, seawater intrusion, drought and climate change. These models include SINTACS (an EPA method), GOD (groundwater occurrence, overlaying lithology, depth to water), PRAST (protective effectiveness, net recharge, aquifer media, soil media and topography), GALDIC (used in coastal aquifers ) and GRiMMS (drought assessment).

Climate Change: Analysing the possible effects of climate change on surface and groundwater on a country or region is challenging. A typical methodology involves: examining climate trends; selecting appropriate climate change models that predicts future risks (e.g. changes in precipitation and temperature); modelling the vulnerability of the area to these risks; and, assessing the potential impact of these changes. In more detail this involves:

    • Climatic Trends. Historic variations and trends in temperature and precipitation can be assessed using Log transformations, descriptive statistics and the Mann-Kendall Trend Test (M-K test). The latter is a non-parametric test (distribution free).
    • Assessment of Risk. Historic data analysis may throw light on future trends. These can then be compared with Global Climate Models (GCMs), created by different agencies sponsored by the Intergovernmental Panel on Climate Change (IPCC), using inferential statistics. Over the last 30-years these data have been summarised and discussed in six assessment reports, referenced by the IPCC as FAR (1990), SAR (1995), TAR (2001), AR4 (2005), AR5 (2013) and AR6 (2021).

Prior to year-2016 the most commonly used Climate Model Inter-comparison Projects (CMIPS) were CMIP3, released in year-2010, and CMIP5 released in year-2013. The CMIP3 and CMIP5 datasets contain output from a large number of different GCMs based on different emission scenarios. The 20 different models created under CMIP3 are collection of story-lines that describes different scenarios for the development of the human population, energy consumption and the proportion of renewable energy to fossil fuels. The 57 CMIP5 models are based on a simpler set of scenarios that use varying paths to reach different levels of greenhouse gas concentrations – or Representative Concentration Pathways (RCPs). Both collections of GCMs have scenarios that range from low to high degrees of climate change. The Fifth Assessment Report (AR5) produced by the IPCC drew heavily on CMIP5. Work on CMIP6 started in year-2016 and is a work in progress. Its main aims included provision of common standards, documentation and guidelines. By year-2021, AR6 had endorsed 23 CMIP6 models with “common data set forcing’s”.

With so many models, to choose from, CMIP advises that:

    • There is no perfect model, always use a selection of at least 4 different GCMs, the more GCMs included, the better. Do not attempt to select a best model for the region of interest.
    • When using multiple climate model simulations for an analysis, always average across climate models as the very last step in the analysis.
    • Do not average across multiple emission scenarios. In this case, averaging will NOT improve the quality of the output because scenarios are entirely different possibilities of future development.
    • There is no one most likely emissions scenario. A good practice is to include a low and high scenario in the analysis to encompass the highest range in uncertainty.
    • Inappropriate applications: Selecting one single model and/or one single future scenario for analysis.
    • Do not expect a downscaled climate simulation to match day-to-day observations. Climate projections are intended to match observations over climate time scales of decades, not days.

Model selection is simplified by the fact that the GCMs are split into three different groups: Group 1 (“Most Reliable”); Group 2 (“New and Interesting”); and Group 3 (“Experimental). For instance, the CMIP5 Group 1 Models reduces the choice of outputs datasets to 28.

GCM model selection can be further honed by investigating prior research that has compared regional or global experimental results against theoretical predications. For instance, Clive Best’s blog presents a comparison of a Hadley Centre/Climatic Research Unit Temperature data (HadCRUT4.6) with CMIP5 RCP scenarios:

HadCRUT global data is very useful because it spans the period 1850 to date on a 5° x 5° grid,  and is provided by month and year without infilling of missing values. Another interesting example is the paper presented by Nature Communications, which compared projections of sea level rises with both global and regional level observations. Their analysis looked at the three different RCP scenarios (RCP2.6 (lowest scenarios with strong mitigation of greenhouse gas emissions), RCP4.5 (middle scenarios) and RCP8.5 (highest scenarios). They concluded that the recent sea level data indicate the world is tracking between RCP4.5 (AR5 RCP4.5 & SROCC RCP4.5) and the worst case scenario of RCP8.5 (AR5 RCP8.5 & SROCC RCP8.5).

Its noted that some of these data and models are constantly being updated and tweaked. For instance, HadCRUT is now on version 5. HadCRUT5 now shows a ~0.1 oC upward shift in their modelled mean annual global temperatures compared to HadCRUT4.6, resulting from new stations being incorporated into their dataset and a reinterpretation of mean values.

    • Vulnerability Assessment. For groundwater this assessment can be achieved using a Numerical Groundwater Model or an Overlay and Index Model and, as appropriate, may need to include for anticipated changes in precipitation, infiltration, recharge, runoff and water demand. A summary of these methods, and techniques for predicting flood flood risks, are discussed here.
    • Potential Impacts. In the tropics and low latitudes a warmer climate will increase evapotranspiration, deplete precipitation, which will cause lower runoff and more droughts. In this scenario, groundwater recharge, storage and levels will fall, base-flow to rivers and springs will drop, vulnerable rivers will dry up and there will be an increased risk of coastal saline intrusion. The extra energy produced by higher sea temperatures will create more severe weather patterns including larger, deeper and more frequent tropical cyclones. Other impacts from such a scenario would likely include rising sea-levels, negative impacts on ecosystems, increased water demands and competition between humans, animals, agriculture and natural vegetation. Similarly, the infrastructure, health and economy of countries would also be harmed, and transboundary water disputes would increase.  However, in some countries positive impacts have been envisaged by climate change. For instance, in northern latitude countries, such as Russia, the anticipated impacts of climate change have been welcomed by “parties” interested in opening up opportunities for development, e.g. by the reduction of tundra and swamp-lands.

Carbon Emissions and Environmental Footprints: The following graphic, sourced from the “Visual Capitalist”, highlights the material impact of carbon emissions from different counties in year-2017.

This shows that the big three emitters (B3E), China (27.2%), the US (14.6%) and India (6.8%), were responsible for nearly half of these emissions. This graphic also highlights the fact that 90% of total emissions occurred over the last 85 years. Also, that the UK, who have a policy of reducing emissions to zero within 30-years, contribute just 1.1% to these emissions.

Conclusions that can be drawn from these data are: only the B3E’s can materially reduce world CO2 emissions by changing their energy and environmental policies; the UK’s zero-carbon policy, in common with other small emitters, will have negligible impact on global emissions; and, China/ India’s contention that they are entitled to continue/ increase the use of fossil fuels, because the west emitted similar amounts of carbon during their industrial revolutions is false. The real reason that CO2 emissions took off in China and India was their exponential population growth, and in the US by its exponential consumerism.

A reduction in our carbon footprint is not an easy fix and will come with serious economic and environmental costs. Currently, the GDP and financial prosperity of world economies is directly linked to oil consumption:

Fossil fuels dominate energy consumption by a huge margin. Replacing these fuels with alternative sources of energy will require technical foresight, efficient planning, vast new infrastructure projects and massive expenditure – and not short-term politically expedient policies – or economies will collapse:

As the World Bank (Daniele La Porta et al, 2017) pointed out “Technologies assumed to populate the clean energy shift … are in fact significantly more material intensive in their composition than current traditional fossil-fuel-based energy supply systems”. Most forms of green energy require roughly comparable quantities of materials in order to build machines that capture nature’s energy (sun, wind, and water). Wind farms come close to matching hydro dams in material consumption, and solar farms outstrip both. In all three cases, the largest share of the tonnage is found in conventional materials such as concrete, steel, and glass. Compared with a natural gas power plant, all three require at least 10 times as many total tons of mined, moved, and converted into machines to deliver the same quantity of energy.

The fundamental challenge with battery-powered electric vehicles (BEV) is the very low energy density of batteries compared with petrol (gasoline), and their material requirements. According to the YouTube channel “Engineering Explained”, in 2018 the energy density (in kWh/L) of petrol, by volume, was 13x better than the best lithium battery (and 26x better than the worst battery). The energy density of petrol, by mass, was 50x better than the best battery (excluding the battery pack).

The World bank and others, such as the University of Technology Sydney (Elsa Dominish et al, 2019), have estimated that under currently proposed energy scenarios BEV’s and turbines will require huge increases in mining in the next 30-years with increased demands for: neodymium (2500%); indium (8000%); cobalt (600%); lithium (2000%); nickel, dysprosium, tellurium (200%–600%); copper (2000%); and, many other ores such as manganese, nickel, cobalt, graphite and aluminium. The International Energy Agency (Fatih Birol, IEA) claims that the auto industry will require 30 times more minerals per year with the switch to BEV, and that “the data shows a looming mismatch between the world’s strengthening climatic ambitions and the availability of critical minerals“.

The scale of these demands ignores the earth materials, which also need to be removed (overburden) and processed (waste) to obtain these minerals and metals. For instance, Cobalt requires 1500 tons of earth to be mined to get one ton of this element.

The green-energy cures being promoted by NGO’s and governments will have significant and unavoidable impacts on water-bodies, the air, the landscape, and on visual and sound environments. Indeed, these impacts might prove to be no better than our current reliance on fossil-fuels – and could be far worse.

Laurence Hecht (2009) presents the augment that the only way to provide sufficient energy for the world’s growing population is to use high energy density fuels, such as uranium. He compared the energy density of uranium fuel to oil, coal and wood and concluded that uranium was vastly superior to other forms of energy. Similar comparisons were provided by the Visual Capitalist in year-2021:

This graphic shows that Uranium has tremendous land, material, energy density, abundance, efficiency and CO2 emission advantages over other fuels. Nuclear accident risks are raised frequently in discussions of the acceptability of nuclear power generation, often framed in the context of the Three Mile Island, Chernobyl and Fukushima accidents. In reality, the safety record of nuclear power plants, by comparison with other electricity generation sources, is good (Our World in Data) .

Wikipedia states that in March 2020 that the worlds population was 7.8 billion, which had a growth rate of 1.2%/yr. By year-2050 its estimated that about 70% of the world’s population will live in megacities. To keep up with this population growth, and movement to cities, huge amounts of additional power are required each year: equivalent to building >3800 Nevada One type solar power concentrators (15 MW), or >2480 Jumilla type solar panel stations (23 MW), or 95 “600 MW-type” coal power stations, or ~57 “1 GW-type” nuclear power stations.

To minimise impacts to the environment and supply people with clean water, sewage treatment, heating, cooling, refrigeration and all the other conveniences of a modern life style then long-term solutions need to prioritise high-energy density fuels and population control.