Population exposure to compound extreme events in India under different emission and population scenarios

“…Although, as seen through our attributions to the results, the SSP5 predicted reasonably hopeful trends for human progress, yet the associated fossil-fuel driven development can significantly hamper progressions in resilience to mitigate climate change challenges, as is stated by Schleussner et al (2021). Although Das et al (2022) mentioned that increase in population exposure to impacts of natural hazards can contribute from climate change, population growth and their interaction, Ma et al (2022) world-in-2050-full-report-feb-2017. pdf), fast population growth could boost the GDP in Pakistan by up to US$3.5 trillion in 2050.…”

Section: Discussionmentioning

confidence: 74%

On the emergence of a predicted climate change signal: When and where it could appear over Pakistan

Khan¹,

Wazir²,

Bokhari³

et al. 2023

EUR J SUSTAIN DEV RES

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Emergence of climate change signal attributed to change in mean temperature can bring serious implications to economic stability of developing countries like Pakistan. Likewise, unawareness of vulnerability in regions of a country can direct mitigation efforts towards unwanted areas instead of towards ones that are genuinely deprived of. To address these two issues for Pakistan, we adopted a compendium of five metrics by using climate model data of near surface mean monthly temperature from output of a general circulation model MRI-ESM2-0 of Meteorological Research Institute (MRI), simulated under historical (1850-2014) and projected (2015-2100) periods for five shared socioeconomic pathways (SSPs) described in the sixth assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) originally published in the year 2021. To identify potential hotspot regions, we used four out of the five metrics i.e., change in mean (DM–vulnerability metric), standard Euclidean distance (SED–vulnerability metric), change in standard deviation (DSD–stability metric), and standard score (Z-Score–stability metric) statistics for regional bounds of Pakistan. To investigate emergence of climate change signal, we computed the fifth metric viz. signal to noise ratio (SNR–agility metric) from time series of the near surface mean monthly temperature and checked how rapidly the subject signal emerged out of variability in the studied data under different scenarios. On the estimation of vulnerability and stability, our results revealed that the Himalayan region of Pakistan (the northeast corner) repeatedly appeared to be the most qualified region to be acclaimed as a hotspot due to its reach to optimal echelons in the associated metrics of the DM (more than four degrees), the SED (up to one), the DSD (close to null) and the Z-Score (close to null) under all the studied SSP scenarios. On the estimation of agility, our results revealed that owing to allegedly sustainable scenarios (with low to medium challenges to mitigation), the SSP1, the SSP2, and the SSP4 delayed the evolution of climate change signal (between 2070 to 2100) by at least two decades as compared to allegedly perplexing (high challenges to mitigation) SSP3 and SSP5 scenarios that accelerated the appearance of the signal by crossing the SNR threshold fairly earlier (between 2040 to 2060) in the 21<sup>st</sup> century. With such knowledge at hand, this scientific contribution can advise policymakers and stakeholder agencies to exercise conversant decisions and to equip themselves with evidence to prioritize and target their resources in an informed way over Pakistan region.

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“…However, SSP2 scenario considers medium conditions, and therefore, populations would be higher than the SSP5 scenario for countries like India . Furthermore, it is also predicted that extreme climate events like combined heat waves and extreme precipitation would worsen in Punjab under the SSP5-RCP 8.5 scenario . Such extreme climate events will disrupt the living and consequently decrease the population.…”

Section: Resultsmentioning

confidence: 99%

Predicting Potential Climate Change Impacts on Groundwater Nitrate Pollution and Risk in an Intensely Cultivated Area of South Asia

et al. 2022

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One of the potential impacts of climate change is enhanced groundwater contamination by geogenic and anthropogenic contaminants. Such impacts should be most evident in areas with high land-use change footprint. Here, we provide a novel documentation of the impact on groundwater nitrate (GW NOd 3 ) pollution with and without climate change in one of the most intensely groundwater-irrigated areas of South Asia (northwest India) as a consequence of changes in land use and agricultural practices at present and predicted future times. We assessed the probabilistic risk of GW NOd 3 pollution considering climate changes under two representative concentration pathways (RCPs), i.e., RCP 4.5 and 8.5 for 2030 and 2040, using a machine learning (Random Forest) framework. We also evaluated variations in GW NOd 3 distribution against a no climate change (NCC) scenario considering 2020 status quo climate conditions. The climate change projections showed that the annual temperatures would rise under both RCPs. The precipitation is predicted to rise by 5% under RCP 8.5 by 2040, while it would decline under RCP 4.5. The predicted scenarios indicate that the areas at high risk of GW NOd 3 pollution will increase to 49 and 50% in 2030 and 66 and 65% in 2040 under RCP 4.5 and 8.5, respectively. These predictions are higher compared to the NCC condition (43% in 2030 and 60% in 2040). However, the areas at high risk can decrease significantly by 2040 with restricted fertilizer usage, especially under the RCP 8.5 scenario. The risk maps identified the central, south, and southeastern parts of the study area to be at persistent high risk of GW NOd 3 pollution. The outcomes show that the climate factors may impose a significant influence on the GW NOd 3 pollution, and if fertilizer inputs and land uses are not managed properly, future climate change scenarios can critically impact the groundwater quality in highly agrarian areas.

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Population exposure to compound extreme events in India under different emission and population scenarios

Cited by 54 publications

References 73 publications

Adaptation to compound climate risks: A systematic global stocktake

Adaptation to compound climate risks: A systematic global stocktake

On the emergence of a predicted climate change signal: When and where it could appear over Pakistan

Predicting Potential Climate Change Impacts on Groundwater Nitrate Pollution and Risk in an Intensely Cultivated Area of South Asia

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