Modelling Agriculture, Forestry and Other Land Use (AFOLU) in response to climate change scenarios for the SAARC nations

Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor

There has been a long-lasting impact of the lockdown imposed due to COVID-19 on several fronts. One such front is climate which has seen several implications. The consequences of climate change owing to this lockdown need to be explored taking into consideration various climatic indicators. Further impact on a local and global level would help the policymakers in drafting effective rules for handling challenges of climate change. For in-depth understanding, a temporal study is being conducted in a phased manner in the New Delhi region taking NO2 concentration and utilizing statistical methods to elaborate the quality of air during the lockdown and compared with a pre-lockdown period. In situ mean values of the NO2 concentration were taken for four different dates, viz. 4th February, 4th March, 4th April, and 25th April 2020. These concentrations were then compared with the Sentinel (5p) data across 36 locations in New Delhi which are found to be promising. The results indicated that the air quality has been improved maximum in Eastern Delhi and the NO2 concentrations were reduced by one-fourth than the pre-lockdown period, and thus, reduced activities due to lockdown have had a significant impact. The result also indicates the preciseness of Sentinel (5p) for NO2 concentrations.

The effects of climate change scenarios on Tilia ssp. in Turkey

Global climate change will cause significant changes in climate parameters, especially temperature increases and changes in precipitation regimes worldwide. Since the life of living things is directly related to climate parameters, this process will inevitably affect all living things. The plants will be the most affected living things from this process because they do not have an effective movement and migration mechanism. Therefore, global climate change will cause significant species and population losses in plants. To minimize the potential loss of species and populations, it is necessary to predetermine the potential changes in species' distribution areas and take necessary actions. Therefore, this study was aimed to determine the distribution areas of three Tilia species (Tilia tomentosa, Tilia cordata, and Tilia platyphyllos), which have economic, ecologic, and social value and show the local distribution in Turkey and to determine how they will be affected by global climate change. Within this scope, nineteen bioclimatic variables, Emberger climate classification, aspect, and topographic altitude variable were used in the modeling process. By modeling the scenarios SSP 245 and SSP 585, the projections were made for 2040, 2060, 2080, and 2100 regarding the areas suitable for the growth of these species and how these areas will change compared to their current situation. The results suggest that the distribution areas of all three Tilia species will change due to climate change, and the area of loss will be 43.5 km² (4%) for T. tomentosa, 9953.6 km² (15%) for T. platyphyllos, and 448.0 km² (19%) for T. cordata. Moreover, a more important point here is that increases and decreases will be observed in their distribution areas, and these changes will occur in a short process and at significant levels. In this case, the migration mechanism that these species will require must be provided by humans.

Spatiotemporal variability and time series trends of rainfall over northwestern parts of Ethiopia: the case of Horro Guduru Wollega Zone

This study examined the variability and trend of rainfall over Horro Guduru Wollega Zone. Studies such as this have paramount importance in countries and areas where rain-fed agriculture is predominant. Datasets for analysis were obtained from the National Meteorological Agency of Ethiopia (NMA) from 1987 to 2016 and Climate Hazard Group InfraRed Precipitation (CHIRPS) 1987-2019 with the station portal. Monthly rainfall with temporal variability ranging from 9.77 to 141.93% was observed. High variable (CV > 30%) and less variable (CV < 20%) rainfall was observed in the CHIRPS data records. Rainfall during most months of the last 30 and 33 years showed a decreasing trend. Rainfalls with temporal variability ranging from 12.7 to 75.92% and from 8.11 to 43.45% were observed during the 3-month seasons, respectively. Rainfall over the 3-month seasons of the last 30 and 33 years showed a decreasing trend. The average total rainfall ranging from 107.203 to 1016.82 mm and from 122.8 to 1147.9 mm, with variability from 9.163 to 55.7% and from 7.831 to 36.68% were observed during the Belg, Kiremt, and Bega seasons of the last 30 and 33 years, respectively. A decrease in rainfall was tested over these three seasons of the last 30 and 33 years. Significantly different (P < 0.05) and less variable (CV < 20%) annual total rainfall was recorded at 24 stations over 30 years. Declining annual rainfall was observed over 30 and 33 years. Non-significantly different (P < 0.05) and less variable (CV < 20%) average decadal rainfall ranging from 1342.6 to 1372.8 mm was observed during the last 33 years. The study area had experienced a rainfall with decreasing trends almost over all time scales. These might have been resulting in failure of agricultural production that necessitates developing and implementing systematic planning and management activities in the crop calendar under the face of changing rainfall patterns.

Microbiological status of drinking water sources and its relationship with human health in Solan, India

In Solan district, the developmental activities associated with chemical based farming, rapid urbanization, and rampant industrialization have led to many diarrhoeal, gastroenteritis, and hepatitis disease outbreaks. This has necessitated for microbiological assessment of indicator organisms, the thermotolerant coliforms, in drinking water sources, and their relationship with diarrhoeal disease. All the 49 Public Health Institutes (PHIs) of the district were categorized into very low, low, moderate, and high disease burden regions by stratification method. For drinking water, 55.5, 16.5, and 17% people preferred springs, borewells, and hand-pump respectively. These sources inventoried by Knowledge, Attitude, and Practice survey in one of very low and seven of high disease burden regions, and were analyzed by multiple tube fermentation technique. A cross-sectional survey of 200 children was undertaken for diarrhoeal disease estimation. Parwanoo, an industrial and Kurgal, a non industrial region witnessed highest (30.20) and lowest (4.40) Most Probable Number (MPN) per 100 ml water of thermotolerant coliforms, respectively. Thermotolerant coliforms were also observed significantly more (16.77 MPN/100 ml water) in monsoon than in post monsoon season (9.04 MPN per 100 ml water). The thermotolerant coliform Escherichia coli was recovered from six and three water sources respectively during monsoon and post monsoon. A strong correlation (r = 0.78) existed between the diarrhoeal disease occurrence and the concentration of thermotolerant coliforms in monsoon whereas it was moderate (r = 0.61) in post monsoon. The study indicated more contamination of water sources due to industrial activities which further got aggravated during the rainy season of the region.