Climate Change - Science topic

Buen dia Jesus!

Your answer is not directly related to the question.

However, concious consumer and environmentally friendly agents of change in the 60s, 70s, 80s, 90s, and 2000s forced society and business and governments towards Rio +20 and shift to green market thinking under green economies and green growth... After the celebration they assimilated most conscious consumers through sustainable development washing and they assimilated environmentally friendly agents of change with Jobs and they went the way of dwarf green markets economics currently being called climate change economics

Hi Wycliffe Tumwesigye here is a script to download data from CMIP6 or CMIP5 using Python that can be useful for you:

"""

! pip install esgf-pyclient==0.3.0

!pip install requests-cache==0.4.1

from pyesgf.search import SearchConnection

import os

import requests_cache

requests_cache.core.CachedSession

#from pyesgf.search import SearchConnection

#import os

#import pandas as pd

import requests

from tqdm import tqdm

import xarray as xr

#import requests_cache

requests_cache.core.CachedSession

lista_modelos= ['ACCESS-CM2','ACCESS-ESM1-5','AWI-CM-1-1-MR','BCC-CSM2-MR',

'CAMS-CSM1-0','CAS-ESM2-0','CMCC-CM2-SR5','CMCC-ESM2','CanESM5',

'EC-Earth3','EC-Earth3-Veg','EC-Earth3-Veg-LR','FGOALS-f3-L',

'GFDL-ESM4','IITM-ESM','INM-CM4-8','INM-CM5-0','IPSL-CM6A-LR',

'KACE-1-0-G','MIROC6','MPI-ESM1-2-HR','MPI-ESM1-2-LR','MRI-ESM2-0',

'NESM3']

conn = SearchConnection('https://esgf-node.llnl.gov/esg-search', distrib=True)

ctx = conn.new_context(project='CMIP6',

experiment_id=['historical'],

realm=['atmos'],

variable='uas',

frequency='mon',

source_type=['AOGCM'],

variant_label='r1i1p1f1',

source_id= lista_modelos

)

ctx.hit_count

ctx.facet_counts['source_id'].keys()

# Obtain urls lists

lista_urls=[]

for i in range(len(ctx.search())):

try:

result = ctx.search()[i]

print(result.dataset_id,'..............ok')

lista_urls.append(result)

except:

pass

print('-------------------------------')

print('Lista finales')

lista_urls

# Download the first model for example

tr=[x for x in lista_urls if lista_modelos[0] in x.dataset_id]

files = tr[0].file_context().search()

lista=[]

for i in range(len(files)):

lista.append(files[i].opendap_url)

print(lista)

ds = xr.open_mfdataset([x for x in lista], chunks={'time': 120}, combine='nested', concat_dim='time')

ds_mei=ds.where((ds.lon>=-90+360) & (ds.lon<=-60+360) &(ds.lat>=6) & (ds.lat<=25),drop=True)

ds_mei=ds_mei.sel(bnds=1)

# Plot example

data = ds_mei.uas[0,:,:]

print(type(data))

data.plot.contourf(levels=35,cmap='jet',add_colorbar=True, x='lon',y='lat');

# Write the netcdf to a route

ds_mei.to_netcdf('uas_'+lista_modelos[0]+'_Historical.nc',format='NETCDF3_64BIT', mode='w')

"""

I hope it helps

Best regards!

Dear friends, here sharing article you may find interested in good faith and in line somehow with the theory around the question at hand from paradigm shift avoidance point of view

Sustainability thought 170: What happens to the Thomas Kuhn’s paradigm evolution loop under willful academic blindness? What are the implications of this?

Dear Takele Taye Desta,

In order to build a climate-resilient economy, the pro-environmental transformation of the classic brown growth linear economy of excess to a sustainable green zero-carbon growth and closed loop economy must be carried out efficiently and as quickly as possible. Whether the negative effects of the increasingly rapid global warming process can be avoided or reduced to a significant extent depends on the timeframe in which the aforementioned process of pro-environmental transformation of the economy is realised. The key issue is the period of the next few years. On the other hand, if this plan is not realised on a global scale within the current decade, it is unfortunately unlikely that the most negative scenario of developments and effects related to climate change will be avoided. In this negative scenario, before the end of the middle of the 21st century, the critical level of CO2 in the atmosphere may be exceeded, resulting in a significant acceleration of the progressive global warming process and the impossibility of reversing or even stopping it. Therefore, during this decade, mankind should implement as much as possible of the above-mentioned plan to carry out a pro-environmental transformation of the economy. The extent to which we reduce the scale of a future climate catastrophe and protect the climate, but also the biodiversity of natural ecosystems, protect the planet's biosphere, depends on this. The conditions under which future generations of people will live and the possibilities of life on planet Earth in general depend on this. For several decades, climatologists, biologists and ecologists have been reporting on the growing risk and scale of a global climate catastrophe, which, according to the latest results of predictive analyses of long-term climate change, may already occur at the end of this 21st century. However, these numerous warnings have been ignored and disregarded for many years in the world of politics and business. In the last few years, things have started to change a little positively on this issue. The number of articles dealing with the issue of climate change and the key role of human civilisation in this issue has increased. There has been an increase in the number of discussions and debates on this issue presented in various media. However, the scale of pro-environmental transformation of the economy, including the green transformation of energy, is still far too low. The level of pro-environmental state interventionism, pro-environmental awareness of citizens, development of green finance, development of emission-free energy sources, etc. is too low. I am conducting research in this area. I have described the key determinants for the necessary, smooth and rapid implementation of the pro-environmental transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero-growth and closed-cycle economy in my scientific work. I have described the issues outlined above in articles posted on my profile of this Research Gate portal. I invite you to collaborate with me on this important issue for the future of the planet's biosphere and climate.

Best regards,

Dariusz

Climate change is a reality, but we must found a reference to be sur about the tendency of change. No one can explain which is the next step for climate change.

The statistical test can not respond to a dynamique change.

Dear Nzeyimana Bahati Shaban . See the following useful RG link:

Dear Lucio,

I too believe that what you have described as the nature of human population dynamics is dependent on the nature of the dynamics of the traditional market structure that serves them. Well, in the short term (months and quarters) it is citizens who adjust their functioning to seasonal changes in the level of production, income, purchases made etc. In the medium term (several to sometimes a dozen years), changes in the rate of economic growth that take place as part of business cycles translate into changes in citizens' income and consumption levels, and this then influences citizens' decisions to start a family and have children. On the other hand, in the longer term (from several years to several decades), the long-term economic processes, the changing sectoral and industry structure of the economy, the significantly changing level of economic development, production, income, etc., translate into significant changes in the living standards of citizens and the prevailing purchasing, housing and living standards. Subsequently, these significant changes in the economic processes taking place, in economic development, including the public products and services offered by the state (education, health care, public utilities, social assistance) and consequently also in the living standards of citizens largely determine the fertility rate, housing standards, the product and service structure of purchases made, the length of the average life expectancy of citizens, possibly also the process of population ageing and other changes in the social structure. Consequently, there are correlations between economic development and structural changes realised in the medium and long term in markets and economic sectors and changes in citizens' living standards, changes in consumption standards, living conditions, economic decisions made, fertility levels, citizens' life expectancy, social processes, etc.

Regards,

Dariusz

Dear Lucio,

In my opinion, the economics of climate change and the economics of a perfect green market are reconcilable, but only in theory. I have described this in my articles. Unfortunately, from theory to reality is a very big gap in this field. For the time being, the process of carrying out a full pro-environmental transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero-growth and closed loop economy to create a zero-carbon economy, to halt the progressive process of global warming, to halt the over-consumption of natural resources, to halt the increase in environmental pollution is not possible with the current political, economic, financial, social, etc. realities. Therefore, in reality, the economics of climate change and the economics of a perfect green market are incompatible, despite the fact that it has been theoretically described how this can be achieved.

Thank you very much,

Best regards,

Dariusz

Clinometer to measure height of trees, camera to photograph light entering sub canopy, traps to collect seeds, bags and jars for samples, tape measure to measure DBH, core sampler if doing dendrochronology, pisometer if determining water tables, gps locater, etc. :)

Remove all forest litter (dead branches from lower parts of trees). It provides the "fuel" for the next "wild" fire.

Dear Mulambwa Mwanang'ono,

Thanks for your reply. Yes, that is correct. It may be that even the current state-of-the-art generations of Big Data Analytics technologies are not yet so perfect that they can significantly help to forecast the future occurrence of specific phenomena composed of multi-faceted, complex, multi-factorial processes. Big Data Analytics technologies are constantly being developed and refined. Computing capacities and the number of data sets are constantly increasing. Therefore, in the future, perhaps a lot more will change in this regard and Big Data Analytics will prove more helpful in predicting the occurrence of complex, multi-factorial phenomena and processes.

Thank you very much,

Greetings,

Dariusz

As noted above, camels are not typically bred to produce meat, but certainly produce milk of high value to local communities. That fact that are managed in extensive grazing models, rather than intensively, means that they will inevitably contribute lower GHG emissions. But they are typically held as wealth assets and as a livelihood component, rather than for high productivity output. As such, they are not really comparable to conventional meat or dairy cattle.

Have a look at the following RG link.

Springer has several options

Revered Professor Dr.Dariusz Prokopowicz,

It is very critical question to everyone to answer because the issues of Climate Change has becoming vigorous in some countries.

The future agriculture will be balanced by the potential areas will have good organic cultivation than harsh, harmful negative effects of the climate change in some countries.

The issues of the climate change may not be global problem right now but it could be one of the major problems in the 22nd century.

Most of the developing countries farmers are becoming vulnerable to manage their cultivation process due to the effect of climate change now a day.

Melting the ices and increasing the sea level and dislocation water bodies, animals are another threatening factor to deeply think about the issues of climate change.

Unless or otherwise any serious effective measures are to be taken against the climate change at global level that could be major problem which will teach a big lesson to the world of human beings in the future.

Prevention is better than cure. It is not only the Researchers, development practitioners worry but also the stakeholders have to think about it in the household level.

The developed countries have to think twice about this climate change issue than others. The agriculture may affect directly due to the effect of the climate change in the future definitely.

The alternatives like Precision agriculture, organic agriculture and conservative agriculture could support the farmers households somehow better than worse.

All these soil and water conservation measures could be implemented with serious watershed management approach and structures among the farming community but the main thing is to control the developed countries interventions on producing carbon CFC more than others.

The objectives of the capitalist countries have to achieve the target if producing the Refrigerators and Air conditioner without thinking the catastrophe of the humans and earth.

This is very pathetic condition to overcome the climate change issue successfully. It needs the collective efforts and thinking to stop against the climate change at macro level.

Agriculture will become question mark to produce the food for consumption. It is difficult to balance the food shortage among the countries in the future.

Agriculture sustainability in terms of foods that will be good sign of economic progress if any countries. Russia is the best example failed to concentrate on agriculture production and how the people managing for their consumption of food.

Sustainable agricultural development and reduce the effect of the climate change as the one if the SDGs 2030 but the serious measures have to be taken against the issue of climate change at global level.

Dear Dr. Jennings,

The philosopher´s stone to energy supply is the “energy mix”. Every type of energy has strong and weak points and the current political reality proves more than any conference this statement.

As far as the climate change and the human impact are concerned , the average of all sorts of natural precipitation and temperature measured over a significant long period of time at a certain area/ zone of the surface of the globe (= climate) is influenced by 4 spheres (from the crust to the core as follows) :

1. Atmosphere with the extra-terrestrial heat source called the sun (moderate to good knowledge) – rather stable during the “Anthropocene” (see also point 4)

2. Lithosphere with the radioactive decay of radioactive elements predominantly U, Th and Bi as the major heat source (moderate to good knowledge) – very stable during the “Anthropocene”

3. Asthenosphere the largest “Underfloor heating system of the globe”. Permanent turbulences –instable during the “Anthropocene” (poor knowledge to unknown)

4. The core responsible for the Earth´s magnetic field controlling orientation of living beings and acting as a protective shield from cosmic rays is very unstable – see the Race of the North Pole towards reversal- during the “Anthropocene” (very poor knowledge to unknown)

This question points to an equation with more than one unknown.

HGD

P.S. the term "Anthopocene" which is not yet accepted as a stratigraphic term is only used as the youngest period of time of Earth´s history.

.

Serigne Mbacké Coly <May be, the following article will be a useful one for your research>

Bahinipati, C.S., Kumar, V., Viswanathan, P.K. and Kavya K (2021): “Estimation of district-wise livelihood vulnerability index for the four coastal states in India”, in: Indrajit Pal., Rajib Shaw., Riyanti Djalante & Sangam Shrestha (Eds.), Disaster Resilience and Sustainability Adaptation for Sustainable Development, Netherlands: Elsevier, pp. 459-488. https://www.sciencedirect.com/science/article/pii/B9780323851954000081

Dear

In my opinion, the economics of climate change is an attempt to present projections of potential future transformations and modifications of economic, socio-economic and financial processes that are likely to take place in the future in connection with the projections of climate change, including, above all, the progressive process of global warming and the various effects generated by these climate changes, most of them negative for nature and humans. To answer your question above: is the economics of climate change ecological economics? - I state that as the concept is new and developing in meaning it is difficult to conclusively determine whether the economics of climate change is an ecological economics. The economics of climate change is an attempt to describe economic processes and to estimate the amounts of financial resources, including additional costs, which will be generated in the future to reduce the scale of the negative social and economic effects of the progressive process of global warming. Estimating such cost amounts for a perspective of a few decades and with an unknown scale of the acceleration of the global warming process is therefore not precise and is subject to a certain level of estimation error. However, attempts are being made to estimate the additional costs that humanity will incur in order to limit, for example, the scale of the decline in food production, the decline in the production of agricultural crops due to the increasing scale of increasingly frequent and persistent periods of drought and the outbreak of forest and agricultural fires. Estimates are also being made of the costs that will have to be incurred in the future in order, for example, to effectively carry out a full pro-environmental transformation of the energy sector in a relatively short period of time in order to significantly reduce CO2 emissions into the atmosphere. This attempts to present the necessary adaptation processes that will have to be carried out in the future in order to adapt civilisation to global warming in economic and financial terms. In addition to this, the high level of variation in the aforementioned estimates of the amounts of costs that humanity will be forced to bear is also due to the adoption of different priorities for the projected adaptation processes, since, on the one hand, the aim of these adaptation processes may be to reduce the negative effects of inevitable climate change or, on the other hand, the key objective of the aforementioned processes of pro-environmental transformation of the economy may be to try to halt the progressive process of global warming and thus avoid the very negative scenario of a global climate catastrophe that may already occur at the end of the current 21st century. However, this latter objective may be difficult to achieve if the pace of implementation of the pro-environmental transformation of the economy is also as slow in the future as it has been so far. If, however, this were the main objective for estimating the aforementioned additional costs that humanity will be forced to bear, estimating the level of decline in economic development, estimating the additional social, health costs caused by climate change, estimating the costs of e.g. irrigation of agricultural fields in a situation of permanently occurring periods of drought, etc., then, in such a situation, the economics of climate change may acquire the attributes of ecological economics or pro-ecological, pro-environmental economics in the future. In a situation where plans are being built to smoothly carry out a pro-environmental transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon, zero-growth and circular economy in order to halt global warming and avoid a negative scenario of a global climate catastrophe, a climate change economy subordinated to these goals may acquire the attributes of pro-environmentalism and sustainability. This will then result in the possibility of such economics being recognised as pro-environmental, pro-environmental, green or ecological economics. The above is the result of my thoughts on this issue and the results of my research on the subject.

Best regards,

Dariusz

Мирза Валид

If the task is a diagnosis, then you are absolutely right. But the climate scale is measured in decades. Thus, by measuring temperature and precipitation on a time scale of weather conditions, in 2042 you will be able to ascertain whether or not there were climate changes in 2022. The cause always appears before the effect. By observing the parameters that cause climate change, you can assess climate change online. It's my opinion.

I strongly believe that everyday political conflict, poor health system and rich climatic conditions are some of the factors that contribute to most of zoonotic outbreaks. One other aspect that we need to look at is the massive gap in "one health" approach, clearly the Veterinary services , eologists etc is poor and no collaborations with the human medical sciences to tackle the problems.

Dear @Collethy Jaru

I have attached one pdf, and shared useful links; hope, these will be useful to you.

ML is a subdivision of AI, so I would recommend using AI (which includes ML) in your written descriptions (unless you are specifically focused on ML). If you write ML and and then use AI, people like me will wonder about your understanding of the two. This article (https://www.dataversity.net/brief-history-artificial-intelligence/) is a quick read and will help in understanding the diffs. The EPA is currently tracking greenhouse gas emissions, which come from a variety of sources, so you can use their data in the grant request. How you're planning to control GGEs with AI is ... a big question mark. Cars, office building and home furnaces, industry, generation of electricity- maybe. Agriculture (cows and rice) probably not. Cars will probably have shifted to 90% electric before you convince manufacturers to install ML programs. I'd guess office buildings and electric companies are places where you could have some impact. One final personal note: If someone says "global warming," don't correct them. Global warming is actually more accurate, describing the entire planet. Climates cover areas of the planet. I have a suspicion oil companies introduced the term "climate change," to confuse the issue and make it sound not quite so bad. With climate change, it sounds like only certain areas will be impacted. Best of luck, K

I gather by the question, there could be some that consider the recent changes in climate due to CO2, global warming, glacial melting, etc. to be outside of natural conditions, so for their research, they may specifically select data before the last several decades and compare it with recent changes. Others might include anthropogenic influences as natural. But otherwise, I seem to agree with Dr. Riese that most researchers or statisticians use the available historical and if available paleo data to estimate risk or extreme events. This is usually done by taking available data, ordering from low to high, and using the number such as 50 years of data to estimate frequency. If we look at paleo indicators, the earth had periods of much higher oceans, and fluctuations through time noticeable by signs or indicators such as coastal terraces and scarps. Some researchers such as Luna Leopold in SW USA looked at available data for cyclic drought indicators as these periods also had the most severe floods, because the vegetative cover was so poor, even though the rainfall was less. Leopold identified that droughts for that area occurred about every 20 years, with lower rain, sparse vegetation, higher flood and sediment extremes. Flow records reviewed for the Suwannee River and other streams in the Okenfenokee Swamp during the 2007 wildfires, suggested the severe wildfires occurred about every 50 years with drought, with lesser wildfires about 20-25 years. A substantial amount of watershed study has been conducted with experimental catchments, where 10 years or more are used to calibrate them such as in stable forest conditions, then activities as reading, timber harvest, agricultural conversion are conducted and changes in hydrology, sediment, etc. are measured through some time period. Stable conditions would be identified by the researcher and typically used for that study locally or perhaps regionally. It would be up to a number of climate scientists that might decide for the earth or broader regions whether stable or baseline conditions might be identified and useful. But in my state, the paleo ocean was at one time about 300 feet higher than present, which is often referred to as the Fall Line. In my several decades here, we have had periods of drought, periods of flooding, and changes in population, land use, etc. Much care, assumptions, data go into forecasting, and with disclosing confidence limits to better qualify. But some significant disturbances such as Hurricane, atmospheric river, large wildfire or abrupt Land use adjustments are not easy to predict.

Springer Journal Suggester or Find journals | Elsevier® JournalFinder might be helpful for you.

You could find a suitable journal from the references list of your article.

Hi,

Read my article (meticulously) and send me a direct. I will guide you.

Icen

As much as possible, determining the provenance of seed sources to be used in reforestation should be supported by seed source movement trials. The evolution of different genetic variants of the same species from different regions occurs in response to a variety of factors, not just mean annual temperature differences. Depending on the driving climate factors in your region, genetic variants of the same species may develop different phenotypic traits based on a wide-range of climate variables that you may not be able to predict a priori: eg., growing season precipitation, mean hottest/coldest month temperatures, average number of growing season days with precipitation, etc. Your management goals should also inform your planting decisions. Are you managing for wood quality/timber production? Rapid growth? Drought resistance? By mixing provenances from different areas without prior testing you may guess correctly which variants may do well in an altered future climate or you may not. Variants you have planted may grow more quickly in a drier, warmer climate, for example, but may experience reductions in wood strength and stiffness that could impact their stability and or commercial value. Any large-scale forest restoration should be back by systematically designed and installed seed source movement trials that seek to identify genetic variants that display specific phenotypic responses to the specific climate scenarios you anticipate will unfold in your geographic region. If such trials are not in place for your species of interest and if it would take too long or be too expensive to implement them, it would make sense to look for seed source movement trials conducted for related species from areas with similar present and anticipated future climate. I also recommend reading the works of Harrington et al. from the northwestern United States for more information on this subject: (https://www.fs.fed.us/pnw/pubs/journals/pnw_2017_harrington001.pdf).

Yes definitely

About 3,500 years ago, that happened in what is now Pakistan to about 5 million people living in 1,000 cities in what we call the Indus Valley civilization. They cut down the trees that were making the rainfall for their area to fire the bricks to build those cities--then the rain stopped and every one of those 1,000 cities were abandoned forever. Fortunately, science learned about 10 years ago, that by replanting the right native plants, we can bring the rain back to areas very quickly. Without replanting the correct native plants, and protecting them from grazing, agriculture and timber harvest, then there is the possibility of ending with a Mars-like rain-free condition.

The general rule that arid lands should use, is set aside 5 hectares of land as Ecological Restoration Preserves for every hectare of grazing land, agriculture land and timber harvest land as you want to have regular rainfall to support the human-utilized areas. Saudi Arabia in 2010 set aside 200 million acres as Ecological Restoration Preserves, based on my suggestion at https://www.ecoseeds.com/cool.html and this year starting the replanting of their whole country with one million tree PER WEEK at

on how to increase the annual rainfall in Libya to about one meter, and those same methods of 1.) native planting, to change the dew point so clouds can form, 2.) rock dams in wadis to slow the flow so water goes into the aquifer instead of running off as flash floods, 3.) Solar panels on every roof to shade the roof and keep the homes cooler plus provide the electricity 4.) rooftop rain water catchment systems on every roof, for flushing toilets and watering gardens, 5.) Cloud seeding either with silver iodine or SNOMAX, and 6.) Replanting the native Pseudomonas host plants that produce the rain clouds, those bacteria that live on leaves of certain plants provide the raindrop nuclei--see https://www.discovermagazine.com/planet-earth/does-rain-come-from-life-in-the-clouds -- are some of the methods that could be tested on a small scale in every country facing water shortages.

There is an excellent paper by Madhuri, Tewari and Bhowmick that computes the LVI for Bihar. It provides a detailed methodology.

Livelihood vulnerability index analysis: An approach to study vulnerability in the context of Bihar

Another interesting article is by Gerlitz et al.

to count the labour hour lost due to climate change.

First, we need to calculate the average productivity lost sector-wise. Then we could proceed towards labour productivity lost and convert the average labour productivity lost into labour hours lost.

Secondly, I could think of 'Labour hour lost due to illness' If there is a method to quantify this then it could be helpful to understand the problem you pose.

Different valuation methods in Environmental economics contextualised to the problem raised with new parameters indices could be another way forward.

Yes, of course, Nigeria for example. In one of my research on the synergy impact between climate change, energy consumption and ecological degradation on the economic growth of Nigeria. Indicates an inverse influence of the population growth to environmental (ecological) degradation via the CO2 emission effect

The best way to display your graphs with variables whose values change is to use the well-known program "Matlab"

Use the plot function inside an iteration chain of variables that takes all the variables' values For more information, see the Matlab book link and you will find the answer

good luck.

Climate change is disrupting weather patterns, leading to extreme weather events, unpredictable water availability, exacerbating water scarcity and contaminating water supplies. Such impacts can drastically affect the quantity and quality of water that children need to survive.

Water and the global climate crisis: 10 things you should know | UNICEF

The cost and benefits of global warming will vary greatly from area to area. For moderate climate change, the balance can be difficult to assess. But the larger the change in climate, the more negative the consequences will become. Global warming will probably make life harder, not easier, for most people. This is mainly because we have already built enormous infrastructure based on the climate we now have.

Climate Q&A - Why is global warming a problem? (nasa.gov)

The numerous negative health effects that have been associated with chemical pesticides include, among other effects, dermatological, gastrointestinal, neurological, carcinogenic, respiratory, reproductive, and endocrine effects. Chemical fertilizer overuse can contribute to soil acidification and soil crust, thereby reducing the content of organic matter, humus content, beneficial species, stunting plant growth, altering the pH of the soil, growing pests, and even leading to the release of greenhouse gases. Farmers in developing countries are experiencing, either short-term or long-term, health effects from exposures to agricultural chemicals, including severe symptoms (e.g. headaches, skin rashes, eye irritations) and some chronic effects (e.g. cancer, endocrine disruption, birth defects).

The main sources of States’ obligations related to climate change are the United Nations Framework Convention on Climate Change (UNFCCC), the Kyoto Protocol, as well as those that may be derived from general international law. International law regulates States’ conduct in relation to their own population only in limited instances.

obligations of state in climatic change - Search (bing.com)

The health sector can play a leadership role in mitigating climatic change- that is reducing its magnitude and consequences. By doing so the health sector will create a series of health, economic and social co-benefits that improve the health of the entire ecosystem in addition to the traditional role of the health sector in the delivery of quality health care. Hospital settings are energy and resource-intensive enterprises that, as they operate today, contribute substantially to climate change.

Procurement, resource use, transportation, biomedical waste management, and other policies and practices contribute to the health sector’s significant climatic footprint.

By effectively managing this footprint and moving towards carbon neutrality, the health sector can demonstrate the way forward in response to climatic change, thereby playing the leadership role in advocating for a healthy and sustainable future as visioned by sustainable development goals. Use of alternative fuels, encouraging walking and cycling, and promoting the use of public transport are some of the simple but effective measures. Conservation of water, and electricity, adopting reduce, reuse, and recycle strategy are some of the other preventive measures

Adaptation at the individual level does not pose any particular problems, although difficulties may arise in each specific case (for example, I myself lived for four years in Florida, it was quite difficult to get used to 35-40 C and 100% humidity in the summer, although in the winter there (at +15) I walked in a shirt with short sleeves and looked with surprise at the "locals" who wore hats and jackets, sometimes even with fur ...). Now I know one native of Africa who lives in the Far North and quite withstands our frosts (confirming the saying "Ural is not the one who does not freeze, but the one who dresses warmly"). Problems will arise more likely at the economic level. Agricultural skills are developed over centuries and are a collective experience that is transmitted at a subconscious level (oranges will not be born from an aspen). All improvements in agricultural technology serve only as an addition to the basic understanding of the essence of the cultivation of a particular crop. In this sense, the experiment has already begun, without any global warming, I saw it in Eastern Europe, where the Brussels "bureaucrats" eliminated traditional agricultural crops in many countries and prescribed the cultivation of others, the characteristics of which the locals had no idea.

If we look at history, the introduction of potatoes into the culture in Russia (and not only in it) met with enormous resistance, until it was freed from bureaucratic diktat. Now it is difficult to imagine Russia without potatoes.

So my recipe is less declarations and instructions, more initiative and ingenuity...

Scholars

Shifting Geographies of Expertise and Policymaking

Dear Thomas,

Yes, there are different estimates on this subject. But according to many research centres, including the IPCC the deforestation process that is still taking place is responsible for min. 1/4 of the increase in CO2 emissions into the atmosphere. Consequently, one of the main factors in reducing greenhouse gas emissions, reducing the scale of the greenhouse effect and slowing the process of global warming includes the aforestation of civilisationally degraded areas, wastelands, post-industrial and mining heaps, etc. As part of aforestations, forests with a multi-species, biodiverse forest ecosystem structure reminiscent of natural forests should be restored and not in the formula of plantation monocultures of forest formations consisting only or mainly of 1-2 tree species. Monocultures are susceptible to various viral, bacterial, fungal diseases and pest attacks. On the other hand, biodiverse forests created in the formula of multi-species forest ecosystems are more resistant to various negative biotic and abiotic environmental factors and contribute more to the local microclimate stabilising the climate of the region, positively influence water transpiration, retain water in the soil, fertilise the soil, provide habitat for many animal species, etc.

Greetings,

Dariusz

Dear Kai,

are you incorporating into your research the study of complex adaptive systems (CAS) and of emergence/emergent phenomena? Both are very strong and robust theoretical concepts in complexity science, which offer powerful methodological tools for analysis.

Best,

Julius

I am not specifically expert in the Mann-Kendall Trend test but it is related to classical non-parametric tests, like the Kendall correlation test that I know better. Be careful with XLSTAT (which works in ExceI, not in Word). Indeed, in the procedure I used a few years ago, I had many problems and had to contact the support. I think you should read more about the test and more generally on non-parametric tests. Asymptotic means when the number of observations n grows to infinity. Otherwise, these tests are based on tables of critical values depending on n. When n is too large, use the asymptotic distribution, often normal with a given mean and a given variance (depending on n, of course). For the continuity correction, it is because the test statistic takes discrete values whereas the asymptotic distribution is continuous. The same kind of correction appears with a binomial distribution. Look in your statistics course.

It's very simple. the term climate covers a time interval of several hundred years. This is true? If so, what global knowledge do we have about the climate in 1700, for example? Measurement of air temperature and pressure at different points on the Earth. discrete changes. Is it true that there were no satellite measurements? Does this mean that the modern system of weather monitoring is still insufficient for studying the climate? The study of climate using atmospheric indices corresponds to the science of 1900. I am simplifying this. what is the atmospheric circulation index? This is a time series of atmospheric pressure differences at two points, for example. If these are observation points in one climatic zone, then this is scientific. And if not? This is about atmospheric circulation indices. Now about teleconnection. Climate change has causes. For example, a volcanic eruption changes the optical characteristics of the atmosphere and cooling sets in. You can study these reasons. We can say that there are no reasons. Everything happens by chance. And then, by insignificant temperature changes in the equatorial zone between Australia and the island of Tahiti, for example, you predict climate change in India. Do you agree that changes in pressure in the equatorial zone cannot be the cause of climate change in India? This is teleconnection, when they study not the causes but the correlation.

Will look forward to your research to find out the results as I am also working on climate change related issues

Dear Kabbilawsh Peruvazhuthi,

Interesting question, which considers two topics: the optimum number of stations and the maximum percentage of missing values.

The optimum number of rainfall stations depends on different factors, for instance the temporal resolution of the measurements (hourly, daily, monthly), the spatial variability of rainfall in a particular area and the purpose/ use of the rainfall data. Hourly measurements generally require smaller spatial scales (and hence more rainfall stations per unit area) than daily or monthly measurements. Areas with a large spatial variability in rainfall (e.g. convective rainfall, tropical areas, mountainous areas) will require more stations per unit area than areas with less spatial variability. Regarding the purpose and use of the rainfall data, it certainly will make a difference whether rainfall data are directly used (e.g. for early warning or trend analyses) or used as input in for instance a hydrological model. In the latter case, the rainfall data are filtered and spatial and temporal rainfall variability is dampened through the rainfall-runoff transformation (i.e. hydrological fluxes and water storage compartments in a catchment). See for instance these papers on appropriate spatial resolutions and number of rainfall stations: , and .

As Vishnuvardan Narayanamurthi also indicated, there is no fixed maximum percentage of missing data. Again, this depends on the spatial and (in particular) temporal variability of rainfall and the use of the data. Highly temporally variable rainfall should have less missing data than more smoothly varying rainfall. One way to look at this is to determine the temporal correlation length by constructing a temporal variogram (temporal correlation coefficient as a function of temporal lag). Temporal resolutions should be typically much smaller than the temporal correlation length and hence, filling data gaps should be done at smaller temporal scales than the temporal correlation length as well (often not much more than a (couple of) day(s) for rainfall). Obviously, when for instance rainfall trend analysis is carried out at larger spatial scales (grid scales instead of station/ point scale), temporal variability will decrease and some more missing values would be acceptable and can be interpolated/ filled in.

Good luck,

Martijn

Dear Sofia,

the CML 2013 impact assessment method also takes ecotoxicity into account, I know. Why do you want to combine impact assessment methods? From a professional point of view, I would like to ask this question because I am interested, I do not want to argue, of course. Best wishes, Viktoria

The following RG links are also very useful:

Deserts are spreading northwards in Central Asia as a result of global warming. A study has found that, since the 1980s, regions with a desert climate have expanded by as much as 100 kilometres in northern Uzbekistan and Kyrgyzstan, in southern Kazakhstan and around the Junggar Basin in northwestern China. The effect of reduced rainfall and warmer temperatures will alter the plants that grow in these regions, and the animals that rely on them...

By this increasing trend of temperature due to climate change it has a huge negative impact on soil biodiversity by means of soil Respiration. At the same time soil Respiration is an important factor by which we can determine biological activities in soil. Also the organic matter decomposition and overall carbon storage in soil.

Dear Lucio,

Answering your question, I say that in my opinion the scale of avoiding the green market paradigm by companies and enterprises is still very large in the country where I operate. Many commercially operating companies and enterprises, if they are not forced by legal norms or if their clients still have a low level of pro-environmental transformation, still ignore the paradigms of the green market, they ignore the principles of ecological social responsibility, the principles of business ethics, green economy, sustainable development goals. On the other hand, some companies, corporations, banks and other financial institutions promote themselves in advertising spots as green and meeting specific goals of sustainable development. This is not always true. Usually, the scale of the transformation of business from classic to green is small and in advertising campaigns certain economic entities present themselves as fully green and implement on a large scale the goals of sustainable development. However, a more serious problem is that this type of misleading customers, citizens, this type of unreliable advertising campaigns and brand promotion campaigns as well as product and / or service offers are also used by government-controlled state-owned companies and some public institutions. The negative effect of such situations is misleading customers and citizens who, when buying products and / or services of a specific company, bank, enterprise, etc., assume that they are buying a green offer from an entity that pursues sustainable development goals and runs a green business, which often does not. is truthful. In addition, companies and enterprises use non-returnable financial subsidies for the implementation of pro-environmental economic ventures, for the creation and implementation of new eco-innovations, new green technologies, etc. However, there is no system of precise determination of what is green innovation and new green technology and what is not. Often, these subsidies are granted to companies and enterprises that fictitiously implement green economic ventures or the scale of pro-environmental business is negligible. On the other hand, there is a lack of financial resources for carrying out a systemic pro-environmental transformation of the economy, for the construction of new power plants generating electricity and / or heat from renewable and emission-free energy sources, for the development of electromobility, for the development of sustainable ecological agriculture, for afforestation of civilization degraded areas, for technology improvement. recycling and creating biodegradable substitutes for plastics, etc.

Best regards,

Dariusz

The observed and projected change in climate is important for assessment and adaptation in field of agriculture. According to our research in the last two decades, the regional land surface warming rate of the past and probably the future has been overestimated, due to the overlook of the urbanization bias in the observational data series of surface air temperature. In China, the bias in surface air temperature data reaches at least 30% for the national meteorological stations. It should be considered in the studies of impact and adaptation of agriculture, in addition to the detection and attribution of climate change. Anyway, almost all the farm lands are not in or near the urban areas, but most of the observational stations in China are.

Dear Ilan

I have been researching dust storms for years. In my opinion, research, participatory management, and regional cooperation can solve the problem to some extent.

Also check please the following useful RG links:

Before answering your valuable question, please let me ask:

The differences between them are greats. They only car that I have now is an electric one. I will not repeat these differences between the two norms of cars that are already known by our honorable colleagues. But, I want to point to another point. These cars are not suitable for petroleum countries where the petrol price is very cheap. My government does not actually encourage them for some reasons that there is no need to be mentioned here. To prove that, the electric stations are mainly only in the capital of Jordan, Amman. If you go to other cities, you will find only zero or one station that can serve two cars at most.!!

For instance, I went to Irbid and wait in the queue for more than 6 hours; otherwise, I should upload my car in the car winch! Anyhow, I will not repeat that black experiment. My beloved car is only for Amman.

My government can solve the problem in few seconds by issuing the following decision: every gas station must have also two electric stations for serving at least two cars simultaneously.

Image' source

1.) Local checklist of the flora, and determine what is native to the area and what is introduced. Do not plant introduced.

2.) "Soil" and the development and creation of "soil" is done by native plants, the soil microbes, and the native wild animals that live among those plants. The animals concentrate nitrogen, phosphorus and calcium for the plants, and move those three nutrients around for the plants.

3.) Each plant that lives on dry land, has a annual rainfall requirement for seedling and adult plant survival and that requirement is within a very narrow range that expands and contracts as you go up and down the annual rainfall totals. It is roughly plus or minus 20%, so rainfall isolines should be drawn to produce plant transfer zones.

4.) Always use local ecotype plant material for planting, because it is better adapted for the soils and weather conditions.

5.) Each plant on dry land, has a soil nutrient and organic matter in the top 4 cm threshold, for seedling survival, and dropping below that threshold even a few PPM will not allow seedlings to survive. Grazing worldwide has dropped those thresholds below what local native plants need to survive, so when seedlings cannot survive, then you end up with barren lands with no or very sparse vegetation.

6.) Do a search for Zombies--if your trees, shrubs, and perennial plants are not reproducing, and you can check that by measuring basal diameters and if no seedlings are found,m then you have a Zombi population that stopped reproducing and that is caused by grazing animals eating the seedlings constantly, or you have lowered the soil nutrients below the survival threshold.

7.) Get established a thin layer of native plants, and that will lower the surface temperatures so that rain clouds can form, and also retain moisture longer in the surface.

8.) Even a very thin layer of native plants on the soil, can keep the soil from getting airborne, which also heats up the air, and eliminates rain cloud formation. See the attached image of the dust off Arabia heating up the air all the way to Pakistan, and eliminating any rain cloud formation

9.) Each country has a group of native plants that are the hosts to the Pseudomonas bacteria, that create our rain clouds for us, because they can form ice crystals at a higher temperature than any other raindrop nuclei. This action only discovered about 12 years ago, and nobody knows what those plants are yet. Have attached an image of the Arabian peninsula, where you can see the Pseudomonas host plants producing clouds, and the atmospheric dust stopping the formation of rain clouds. See https://www.discovermagazine.com/planet-earth/does-rain-come-from-life-in-the-clouds

10.) Get a significant annual budget to do small scale test plots, because each ecosystem has about 1,000-2,000 native plants, and you need to sort out the best two dozen to work with.

11.) Follow the lead of KSA's project that I started at www.ecoseeds.com/cool.html 20 years ago, that is getting funded right now to plant one million trees a week for the next eight years, and over time, plant 10 BILLION across all of Arabia, at https://www.saudigreeninitiative.org/targets/greening-saudi/

If you define better what you mean by "Recovery" that might get you clearer answers.

Think of some indicators (independent variables) like swt, pH, salinity, DO etc and dependent variable like CI of fish (species-wise), distribution, community structure and have a correlation study

Just collect the data and maps, interpolate the data with satellite images through ArcView GIS software

www.geasci.org/IntErO Predicting sediment yield at the catchment scale is one of the main challenges in geomorphologic research. The research of the calculation of soil erosion intensity and torrents in Yugoslavia was initiated by the team of the researchers from the Jaroslav Cerni Institute for the Development of Water Resources in 1947. The first method that was developed in Yugoslavia was the Method for the Quantitative Classification of Erosion - MQCE (1954). The erosion intensity from the river basin was calculated by computing the amount of sediment that reaches the downstream part at the lowest point of the basin (H min). The process of the methodology development for investigation erosion process, mapping, sediment calculating and torrent classification continuous and resulted with the establishment of the Erosion Potential Method – EPM in 1968. The IntErO model (Spalevic, 2011) uses the Erosion Potential Method (Gavrilovic, 1972) in its algorithm background. The IntErO model, an upgrading of the Surface and Distance Measuring (Spalevic, 1999; Spalevic et al, 1999) and River Basins (Spalevic, 1999; Spalevic et al, 2000) programs and can be used for handling a large number of data with the processing of 27 inputs, returning, after the calculations, 22 final result parameters (Coefficient of the river basin form, A; Coefficient of the watershed development, m; Average river basin width, B; (A)symmetry of the river basin, a; Density of the river network of the basin, G; Coefficient of the river basin tortuousness, K; Average river basin altitude, Hsr; Average elevation difference of the river basin, D; Average river basin decline, Isr; The height of the local erosion base of the river basin, Hleb; Coefficient of the erosion energy of the river basin’s relief, Er; Coefficient of the region’s permeability, S1; Coefficient of the vegetation cover, S2; Analytical presentation of the water retention in inflow, W; Energetic potential of water flow during torrent rains, 2×gDF^½; Maximal outflow from the river basin, Qmax; Temperature coefficient of the region, T; Coefficient of the river basin erosion, Z; Production of erosion material in the river basin, Wyear; Coefficient of the deposit retention, Ru; Real soil losses, Gsp; Real soil losses per km2. For calculations model needs the following NUMERICAL VALUES as inputs: (1) The surface of River basin area, F [km²]; (2) The length of the watershed (perimeter), O [km]; (3) Natural length of the main watercourse, Lv [km]; (4) The shortest distance between the fountainhead and mouth, Lm [km]; (5) The total length of the main watercourse with tributaries of I and II class, ΣL [km]; (6) River basin length measured by a series of parallel lines, Lb [km]; (7) The area of the larger river basin part, Fv [km²]; (8) The area of the smaller river basin part, Fm [km²]; (9) Contour lines length, Liz [km]; (10) The area between the two neighboring contour lines, fiz [km²]. The model considers factors related to lithology (rocks permeability by percentage: fp, permeable; fpp, semipermeable; fo, low permeability) and soil type (erodibility coefficient, Y); topographic and relief data (I coefficient), monthly mean and annual precipitation (P coefficient), temperatures annual averages (t coefficient); land cover data (Xa coefficient of the River basin planning): 1. Bare lands; 2. Plough-lands; 3. Meadows; 4. Mountain pastures; 5. Orchards and vineyards; 6. Degraded forests; 7. Well-constituted forests; and finally the state of erosion patterns, and development of the watercourse network (Φ coefficient). The IntErO model can be characterized as semi-quantitative because it is based on a combination of descriptive and quantitative procedures. Compared to other semi-quantitative methods, this is the most quantitative because it uses descriptive evaluation for three parameters only: soil erodibility, soil protection, and the extent of erosion in the catchment.

SOME EXAMPLES OF THE IntErO APPLICATION: Spalevic, V.; Barovic, G.; Vujacic, D.; Curovic, M.; Behzadfar, M.; Djurovic, N.; Dudic, B.; Billi, P. The Impact of Land Use Changes on Soil Erosion in the River Basin of Miocki Potok, Montenegro. Water 2020, 12, 2973. https://doi.org/10.3390/w12112973 Sakuno, N.R.R., Guicardi, A.C.F., Spalevic, V., Avanzi, J.C., Silva, M.L.N., Mincato, R.L. (2020): Adaptation and application of the erosion potential method for tropical soils. Revista Ciência Agronômica, 51(1):  e20186545. Epub February 03, 2020. Link: http://www.scielo.br/pdf/rca/v51n1/1806-6690-rca-51-01-e20186545.pdf Mohammadi, M.; Khaledi Darvishan, A.K.; Spalevic, V.; Dudic, B.; Billi, P. Analysis of the Impact of Land Use Changes on Soil Erosion Intensity and Sediment Yield Using the IntErO Model in the Talar Watershed of Iran. Water 2021, 13, 881. https://doi.org/10.3390/w13060881 Ouallali, A,; Aassoumi, H.; Moukhchane, M.; Moumou, A.; Houssni, M.; Spalevic, V.; Keesstra, S. (2020) Sediment mobilization study on Cretaceous, Tertiary and Quaternary lithological formations of an external Rif catchment, Morocco, Hydrological Sciences Journal, 65:9, 1568-1582, https://doi.org/10.1080/02626667.2020.1755435 (link to download the peper) Spalevic, V., Zejak, D., Curovic, M., Glisic, I., Radovic, A. (2021): Analysis of the impact of fruit growing development on the intensity of soil erosion and runoff: Case study of Krusevo, Bijelo Polje, Montenegro. Agriculture and Forestry, 67 (2): 37-51 (link to download the paper) Tavares, A.S.; Uagoda, R.E.S.; Spalevic, V.; Mincato, R.L. (2021): Analysis of the erosion potential and sediment yield using the IntErO model in an experimental watershed dominated by karst in Brazil. Agriculture and Forestry, 67 (2): 153-16 (link to download the paper) Spalevic, V. (2019): Assessment of soil erosion processes by using the ‘IntErO’ model: Case study of the Duboki Potok, Montenegro. Journal of Environmental Protection and Ecology 20 (2): 657–665. Link to the paper: http://www.jepe-journal.info/journal-content/vol-20-no2 Direct link to the paper: (link) Chalise, D.; Kumar, L.; Spalevic, V.; Skataric, G. Estimation of Sediment Yield and Maximum Outflow Using the IntErO Model in the Sarada River Basin of Nepal. Water 2019, 11, 952. https://doi.org/10.3390/w11050952 Khaledi Darvishan, A., Mohammadi, M., Skataric, G., Popovic, S., Behzadfar, M., Rodolfo Ribeiro Sakuno, N., Luiz Mincato, R., Spalevic, V. (2019): Assessment of soil erosion, sediment yield and maximum outflow, using IntErO model (Case study: S8-IntA Shirindarreh Watershed, Iran). Agriculture and Forestry, 65 (4), 203-210. https://doi.org/10.17707/AgricultForest.65.4.18 El Mouatassime, S., Boukdir, A., Karaoui, I., Skataric, G., Nacka, M., Khaledi Darvishan, A., Sestras, P., Spalevic, V. (2019): Modelling of soil erosion processes and runoff for sustainable watershed management: Case study Oued el Abid Watershed, Morocco. Agriculture and Forestry 65 (4), 241-250. https://doi.org/10.17707/AgricultForest.65.4.22 Nikolic, G., Spalevic, V., Curovic, M., Khaledi Darvishan, A., Skataric, G., Pajic, M., Kavian, A., & Tanaskovik, V. (2018). Variability of Soil Erosion Intensity Due to Vegetation Cover Changes: Case Study of Orahovacka Rijeka, Montenegro. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 47(1), 237-248. https://doi.org/10.15835/nbha47111310 Khaledi Darvishan, A., Derikvandi, M., Aliramaee, R., Khorsand, M., Spalevic, V., Gholami, L., Vujacic, D. (2018): Efficiency of INTERO model to predict soil erosion intensity and sediment yield in Khamsan representative watershed (West of Iran). AGROFOR International Journal, 3 (2): 22-31. https://doi.org/10.7251/AGRENG1802022K Vujacic, D., Barovic, G., Djekovic, V., Andjelkovic, A., Khaledi Darvishan, A., Gholami, L., Jovanovic, M. and Spalevic, V. (2017): Calculation of Sediment Yield using the “River Basin” and “Surface and Distance” Models: A Case Study of the Sheremetski Potok Watershed, Montenegro. Journal of Environmental Protection and Ecology, 18(3): 1193-1202. Link: http://www.jepe-journal.info/journal-content/vol-18-no-3 Spalevic, V., Lakicevic, M., Radanovic, D., Billi, P., Barovic, G., Vujacic, D., Sestras, P., Khaledi Darvishan, A. (2017): Ecological-Economic (Eco-Eco) modelling in the river basins of Mountainous regions: Impact of land cover changes on sediment yield in the Velicka Rijeka in Montenegro. Notulae Botanicae Horti Agrobotanici Cluj-Napoca: 45(2):602-610. https://doi.org/10.15835/nbha45210695 Spalevic, V., Radanovic, D., Skataric, G., Billi. P., Barovic, G., Curovic, M., Sestras, P., and Khaledi Darvishan A. (2017): Ecological-economic (eco-eco) modelling in the mountainous river basins: Impact of land cover changes on soil erosion. Agriculture and Forestry, 63 (4): 9-25. https://doi.org/10.17707/AgricultForest.63.4.01 Khaledi Darvishan A., Behzadfar M., Spalevic V., Kalonde P., Ouallali A., Mouatassime E. S., (2017) Calculation of sediment yield in the S2-1 watershed of the Shirindareh river basin, Iran, Agriculture and Forestry, 63 (3): 23-32. https://doi.org/10.17707/AgricultForest.63.3.03 Vujacic, D., Spalevic, V. (2016): Assessment of Runoff and Soil Erosion in the Radulicka Rijeka Watershed, Polimlje, Montenegro. Agriculture and Forestry, 62 (2): 283-292. https://doi.org/10.17707/AgricultForest.62.2.25 Spalevic, V., Curovic, M., Barovic, G., Vujacic, D., Tunguz, V. and Djurovic, N. (2015): Soil erosion in the river basin of Provala, Montenegro. Agriculture and Forestry, 61(4): 133-143. https://doi.org/10.17707/AgricultForest.61.4.14 Barovic, G. and Spalevic, V. (2015): Calculation of runoff and soil erosion intensity in the Rakljanska Rijeka watershed, Polimlje, Montenegro. Agriculture and Forestry, 61(4): 109-115. https://doi.org/10.17707/AgricultForest.61.4.11 Barovic, G., Leandro Naves Silva, M., Veloso Gomes Batista, P., Vujacic, D., Soares Souza, W., Cesar Avanzi, J., Behzadfar M., Spalevic, V. (2015): Estimation of sediment yield using the IntErO model in the S1-5 Watershed of the Shirindareh River Basin, Iran. Agriculture and Forestry (61): 3: 233-243. https://doi.org/10.17707/AgricultForest.61.3.23 Vujacic, D., Barovic, G., Tanaskovikj, V., Kisic, I., Song, X., Silva, M.L.N. and Spalevic, V. (2015). Calculation of runoff and sediment yield in the Pisevska Rijeka Watershed, Polimlje, Montenegro. Agriculture and Forestry, 61 (2): 225-234. https://doi.org/10.17707/AgricultForest.61.2.20 Behzadfar, M., Tazioli, A., Vukelic-Shutoska, M., Simunic, I. Spalevic, V. (2014): Calculation of sediment yield in the S1 - 1 Watershed, Shirindareh Watershed, Iran. Agriculture and Forestry, 60 (4): 207-216. Link: http://www.agricultforest.ac.me/paper.php?journal_id=185&id=2355 Spalevic, V., Railic, B., Djekovic, V., Andjelkovovic, A. and Curovic, M. (2014): Calculation of the Soil Erosion Intensity and Runoff of the Lapnjak Watershed, Polimlje, Montenegro. Agriculture and Forestry, 60 (2): 261- 271. Link: http://www.agricultforest.ac.me/paper.php?journal_id=182&id=2300 Spalevic, V., Radanovic, D., Behzadfar, M., Djekovic, V., Andjelkovic, A., Milosevic, N (2014): Calculation of the sediment yield of the Trebacka rijeka, Polimlje, Montenegro. Agriculture and Forestry, 60 (1): 259-272. Link: http://www.agricultforest.ac.me/paper.php?journal_id=181&id=2255 Spalevic, V., Hubl, J. Hasenauer, H. and Curovic, M. (2014): Calculation of soil erosion intensity in the Bosnjak Watershed, Polimlje River Basin, Montenegro. The 5th International Symposium “Agrosym 2014”, Jahorina, 23-26 October 2014, Bosnia and Herzegovina, p 730-738. Spalevic, V., Grbovic, K., Gligorevic, K., Curovic, M. and Billi, P. (2013): Calculation of runoff and soil erosion on the Tifran watershed, Polimlje, North-East of Montenegro. Agriculture and Forestry, 59 (4): 5-17. Link: http://www.agricultforest.ac.me/paper.php?journal_id=176&id=2212 Spalevic, V., Simunic, I., Vukelic-Sutoska, M., Uzen, N., Curovic, M. (2013): Prediction of the soil erosion intensity from the River Basin Navotinski, Polimlje (Northeast Montenegro). Agriculture and Forestry, 59 (2): 9-20. Link: http://www.agricultforest.ac.me/paper.php?journal_id=174&id=2167 Spalevic, V., Mahoney, W., Djurovic, N., Uzen, U. and Curovic, M. (2012): Calculation of soil erosion intensity and maximum outflow from the Rovacki River Basin, Montenegro. Agriculture and Forestry, 58(3): 7-21. Link: http://www.agricultforest.ac.me/paper.php?journal_id=171&id=2108 Spalevic, V., Curovic, M., Borota, D. and Fustic, B. (2012): Soil erosion in the River Basin Zeljeznica, area of Bar, Montenegro. Agriculture and Forestry, 54 (1-4): 5-24. Link: http://www.agricultforest.ac.me/paper.php?journal_id=157&id=2015

The following links are also very useful: https://stateoftalent.org/topic/fa7413-how-to-determine-sample-size-for-unknown-population

Although humanity as a whole is more aware than ever of the negative effects of climate change, we’re edging ever closer to the tipping point. The damage from irreversible climate change is expected to impact virtually every industry on Earth, including housing.

Thanks to climate change, renters and homeowners alike, especially young people, are facing a radically different future than we may have imagined. The unfortunate reality is that, unless governments and policymakers take drastic steps toward improving planetary health, climate change will continue to impact everyday life, including where we live...

And it will still cause many side effects since Kyoto/92 is not being observed by nations, specially historical colonizators.

Prior to 1990 the halogenated coumpounds were a pretty big component of greenhouse gases.

The banning of these have been a success story for the GHG and ozone hole stabilization.

After carbon dioxide methane then nitrous oxides are the most important.

When dealing with the overall warming issue the important thing is the gross emissions jmust substract the sequestrations to get the net continuing effect.

The warming of the environment is driving emissions higher because of the melting of the tundra.

To resolve a runaway greenhouse gas effect on global warming the simply reding of emissions will not be effective beside the reduction of emissions we need to more effective in the sequestration.

Methane needs better focus on the losses from the gas lines and the use of a new generation of methane combustion which can make methan a low carbon resource.

Much methane is related to our global agriculture rice and ruminants and efforts to reduce those are needed.

Nitroous oxides are largely related to fertilizer usage.

The way to address the overall issue is to reduce the emissions sources and accelerate sequestations through our management of agriculture forests and marine resources.

We are able to quantify both emissions and sequestrations and develop invcentives and penalties which will provide a way to address the issues.

Thank you, I will try it.

Dear Elaheh, There are significant gaps in knowledge of science of soil conservation and operational strategies, both of which influence to potentially unhealthy soil. To optimise growing international soils sustainably, solid policy support is required. So raising civil and policies and practises knowledge of the crucial significance of soil biological diversity, as well as raising knowledge and understanding about how these soils can be preserved and intended to protect on a global basis, can aid in the achievement of the SDGs.

A seven-day forecast can accurately predict the weather about 80 percent of the time and a five-day forecast can accurately predict the weather approximately 90 percent of the time. However, a 10-day—or longer—forecast is only right about half the time.

But Extreme Weather Prediction models are yet to reach accuracy

Please also see the following RG links.