Green finance is inextricably linked to investment risk, particularly in emerging and developing economies (EMDE). This study uses the difference in differences (DID) method to evaluate the mean causal effects of a treatment on an outcome of the determinants of scaling up green financing and climate change mitigation in the N-11 countries from 2005 to 2019. After analyzing with a dummy for the treated countries, it was confirmed that the outcome covariates: rescon (renewable energy sources consumption), population, FDI, CO2, inflation, technical corporation grants, domestic credit to the private sector, and research and development are very significant in promoting green financing and climate change mitigation in the study countries. The probit regression results give a different outcome, as rescon, FID, CO2, Human Development Index (HDI), and investment in the energy sector by the private sector that will likely have an impact on the green financing and climate change mitigation of the study countries. Furthermore, after matching the analysis through the nearest neighbor matching, kernel matching, and radius matching, it produced mixed results for both the treated and the untreated countries. Either group experienced an improvement in green financing and climate change mitigation or a decrease. Overall, the DID showed no significant difference among the countries.
Precipitation patterns are changing across the globe causing more severe and frequent drought for many forest ecosystems. Although research has focused on the resistance of tree populations and communities to these novel precipitation regimes, resilience of forests is also contingent on recovery following drought, which remains poorly understood, especially in aseasonal tropical forests. We used rainfall exclusion shelters to manipulate the interannual frequency of drought for diverse seedling communities in a tropical forest and assessed resistance, recovery and resilience of seedling growth and mortality relative to everwet conditions. We found seedlings exposed to recurrent periods of drought altered their growth rates throughout the year relative to seedlings in everwet conditions. During drought periods, seedlings grew slower than seedlings in everwet conditions (i.e., resistance phase) while compensating with faster growth after drought (i.e., recovery phase). However, the response to frequent drought was species dependent as some species grew significantly slower with frequent drought relative to everwet conditions while others grew faster with frequent drought due to overcompensating growth during the recovery phase. In contrast, mortality was unrelated to rainfall conditions and instead correlated with differences in light. Intra-annual plasticity of growth and increased annual growth of some species led to an overall maintenance of growth rates of tropical seedling communities in response to more frequent drought. These results suggest these communities can potentially adapt to predicted climate change scenarios and that plasticity in the growth of species, and not solely changes in mortality rates among species, may contribute to shifts in community composition under drought.
Arthropod-borne viruses (arboviruses) are important causes of human disease nearly worldwide. All arboviruses circulate among wild animals, and many cause disease after spillover transmission to humans and agriculturally important domestic animals that are incidental or dead-end hosts. Viruses such as dengue (DENV) and chikungunya (CHIKV) that have lost the requirement for enzootic amplification now produce extensive epidemics in tropical urban centers. Many arboviruses recently have increased in importance as human and veterinary pathogens using a variety of mechanisms. Beginning in 1999, West Nile virus (WNV) underwent a dramatic geographic expansion into the Americas. High amplification associated with avian virulence coupled with adaptation for replication at higher temperatures in mosquito vectors, has caused the largest epidemic of arboviral encephalitis ever reported in the Americas. Japanese encephalitis virus (JEV), the most frequent arboviral cause of encephalitis worldwide, has spread throughout most of Asia and as far south as Australia from its putative origin in Indonesia and Malaysia. JEV has caused major epidemics as it invaded new areas, often enabled by rice culture and amplification in domesticated swine. Rift Valley fever virus (RVFV), another arbovirus that infects humans after amplification in domesticated animals, undergoes epizootic transmission during wet years following droughts. Warming of the Indian Ocean, linked to the El Niño-Southern Oscillation in the Pacific, leads to heavy rainfall in east Africa inundating surface pools and vertically infected mosquito eggs laid during previous seasons. Like WNV, JEV and RVFV could become epizootic and epidemic in the Americas if introduced unintentionally via commerce or intentionally for nefarious purposes. Climate warming also could facilitate the expansion of the distributions of many arboviruses, as documented for bluetongue viruses (BTV), major pathogens of ruminants. BTV, especially BTV-8, invaded Europe after climate warming and enabled the major midge vector to expand is distribution northward into southern Europe, extending the transmission season and vectorial capacity of local midge species. Perhaps the greatest health risk of arboviral emergence comes from extensive tropical urbanization and the colonization of this expanding habitat by the highly anthropophilic (attracted to humans) mosquito, Aedes aegypti. These factors led to the emergence of permanent endemic cycles of urban DENV and CHIKV, as well as seasonal interhuman transmission of yellow fever virus. The recent invasion into the Americas, Europe and Africa by Aedes albopictus, an important CHIKV and secondary DENV vector, could enhance urban transmission of these viruses in tropical as well as temperate regions. The minimal requirements for sustained endemic arbovirus transmission, adequate human viremia and vector competence of Ae. aegypti and/or Ae. albopictus, may be met by two other viruses with the potential to become major human pathogens: Venezuelan equine encephalitis virus, already an important cause of neurological disease in humans and equids throughout the Americas, and Mayaro virus, a close relative of CHIKV that produces a comparably debilitating arthralgic disease in South America. Further research is needed to understand the potential of these and other arboviruses to emerge in the future, invade new geographic areas, and become important public and veterinary health problems.
The relationship between greenhouse gas emission and climate change has led to research to identify and manage the natural sources and sinks of the gases. CO2, CH4, and N2O have an anthropic source and of these CO2 is the least effective in trapping long wave radiation. Soil carbon sequestration can best be described as a process of removing carbon dioxide from the atmosphere and relocating into soils in a form that is not readily released back into the atmosphere. The purpose of this study is to estimate carbon stocks available under current conditions in Sarawak, Malaysia. SOC estimates are made for a standard depth of 100 cm unless the soil by definition is less than this depth, as in the case of lithic subgroups. Among the mineral soils, Inceptisols tend to generally have the highest carbon contents (about 25 kg m(-2) m(-1)), while Oxisols and Ultisols rate second (about 10-15 kg m(-2) m(-1)). The Oxisols store a good amount of carbon because of an appreciable time-frame to sequester carbon and possibly lower decomposition rates for the organic carbon that is found at 1m depths. Wet soils such as peatlands tend to store significant amounts of carbon. The highest values estimated for such soils are about 114 kg m(-2) m(-1). Such appreciable amounts can also be found in the Aquepts. In conclusion, it is pertinent to recognize that degradation of the carbon pool, just like desertification, is a real process and that this irreversible process must be addressed immediately. Therefore, appropriate soil management practices should be instituted to sequester large masses of soil carbon on an annual basis. This knowledge can be used effectively to formulate strategies to prevent forest fires and clearing: two processes that can quickly release sequestered carbon to the atmosphere in an almost irreversible manner.
This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.
This study critically evaluates two COP proposals on Malaysia that have been under consideration to reduce climate damage. A top-down disaggregation framework deploying an "Empirical Regional Downscaling Dynamic Integrated Model of Climate and the Economy" is used to evaluate the local government climate roadmap and Malaysia's emissions reduction agendas under COP21 and subsequently COP22 proposals. The findings show that the costs from climate damage over the period 2010-2110 under the Malaysian Optimal Climate Action scenario will amount to MYR5,483 (US$1589) billion. The commensurate climate damage costs under the COP21 and COP22 scenario would be MYR5, 264 (US$1526) billion. Thus, the effective proposal for reducing climate damage in Malaysia over the period 2010-2110 is the COP22 time-adjusted COP21 proposal but there are a number of macroeconomic cost implications for savings and consumption that policy makers must address before acting.
Environmental nongovernmental organizations (ENGOs) are considered key players for engendering good climate change governance to address both climate change and sustainable development. The participation of ENGOs in climate change governance occurs in a four-phase policy cycle. They include (1) identification of policy options, (2) policy formulation, (3) policy implementation, and (4) policy monitoring and evaluation. The ENGOs, however, have been criticized for their lack of effectiveness, and their roles in tackling climate change remain unclear. To date, the study on the roles and activities of Southeast Asian ENGOs in climate change governance has been under-researched. This study, therefore, applies a systematic literature review of 19 published articles from Scopus and Web of Science-indexed journal to understand the current state of the Southeast Asian ENGOs participation in climate change governance based on the four-phase policy cycle. The findings show that the ENGOs in Southeast Asia are involved directly and indirectly in climate change governance. They are significant actors in the implementation of the climate change policy, but they play a minimal role in the formulation of said policy. It implies that they could also be a vital partner to the government in the climate change governance process as they can bring effective policy improvements. Lastly, this review will recommend future avenues of research for scholars.
Carbon capture technologies are becoming increasingly crucial in addressing global climate change issues by lowering CO2 emissions from industrial and power generation activities. Post-combustion carbon capture, which uses membranes instead of adsorbents, has emerged as one of promising and environmentally friendly approaches among these technologies. The operation of membrane technology is based on the premise of selectively separating CO2 from flue gas emissions. This provides a number of different benefits, including improved energy efficiency and decreased costs of operation. Because of its adaptability to changing conditions and its low impact on the surrounding ecosystem, it is an appealing choice for a diverse array of uses. However, there are still issues to be resolved, such as those pertaining to establishing a high selectivity, membrane degradation, and the costs of the necessary materials. In this article, we evaluate and explore the prospective applications and roles of membrane technologies to control climate change by post-combustion carbon capturing. The primary proposition suggests that the utilization of membrane-based carbon capture has the potential to make a substantial impact in mitigating CO2 emissions originating from industrial and power production activities. This is due to its heightened ability to selectively absorb carbon, better efficiency in energy consumption, and its flexibility to various applications. The forthcoming challenges and potential associated with the application of membranes in post-carbon capture are also discussed.
Institutions for environmental governance evolve differently across sectors. They also vary in the same sector when governments at two levels (national and subnational) have different political alignments. As the policy environment becomes more complex, with global problems like climate change, and politics more dividing, better coordination among various levels of government is a tough governance challenge. Scholars and practitioners need to realize how best to build institutions to bridge the various levels of government in different political environments and environmental sectors. This research analyzes the influence of intergovernmental relations in two environmental sectors in two localities with contrasting political alignments between two levels of government. It draws lessons from solid waste management and climate policy in two Malaysian states (Johor and Penang). In an evolving State and new policy arenas, when formal institutions for intergovernmental relations may not be effectively in place, politics play an even larger role through the discretionary power of federal and subnational authorities. An open political process can help with the engagement of different political groups and civil society to bring legitimacy, resources and efficiency to environmental management, if it is done with robust intergovernmental institutions; otherwise, intergovernmental relations can also become a tool for zero-sum games, cronyism and patrimonialism, which can undermine policies, and result in inefficiencies and ineffectiveness in environmental management.
Seagrasses have the ability to contribute towards climate change mitigation, through large organic carbon (Corg) sinks within their ecosystems. Although the importance of blue carbon within these ecosystems has been addressed in some countries of Southeast Asia, the regional and national inventories with the application of nature-based solutions are lacking. In this study, we aim to estimate national coastal blue carbon stocks in the seagrass ecosystems in the countries of Southeast Asia including the Andaman and Nicobar Islands of India. This study further assesses the potential of conservation and restoration practices and highlights the seagrass meadows as nature-based solution for climate change mitigation. The average value of the total carbon storage within seagrass meadows of this region is 121.95 ± 76.11 Mg ha-1 (average ± SD) and the total Corg stock of the seagrass meadows of this region was 429.11 ± 111.88 Tg, with the highest Corg stock in the Philippines (78%). The seagrass meadows of this region have the capacity to accumulate 5.85-6.80 Tg C year-1, which accounts for $214.6-249.4 million USD. Under the current rate of decline of 2.82%, the seagrass meadows are emitting 1.65-2.08 Tg of CO2 year-1 and the economic value of these losses accounts for $21.42-24.96 million USD. The potential of the seagrass meadows to the offset current CO2 emissions varies across the region, with the highest contribution to offset is in the seagrass meadows of the Philippines (11.71%). Current national policies and commitments of nationally determined contributions do not include blue carbon ecosystems as climate mitigation measures, even though these ecosystems can contribute up to 7.03% of the countries' reduction goal of CO2 emissions by 2030. The results of this study highlight and promote the potential of the southeast Asian seagrass meadows to national and international agencies as a practical scheme for nature-based solutions for climate change mitigation.
Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatially and temporally. The problem becomes more complex as drought occurrence is dependent on a multitude of factors ranging from hydro-meteorological to climatic variables. A paradigm shift happened in this field when it was found that the inclusion of climatic variables in the data-driven prediction model improves the accuracy. However, this understanding has been primarily using statistical metrics used to measure the model accuracy. The present work tries to explore this finding using an explainable artificial intelligence (XAI) model. The explainable deep learning model development and comparative analysis were performed using known understandings drawn from physical-based models. The work also tries to explore how the model achieves specific results at different spatio-temporal intervals, enabling us to understand the local interactions among the predictors for different drought conditions and drought periods. The drought index used in the study is Standard Precipitation Index (SPI) at 12 month scales applied for five different regions in New South Wales, Australia, with the explainable algorithm being SHapley Additive exPlanations (SHAP). The conclusions drawn from SHAP plots depict the importance of climatic variables at a monthly scale and varying ranges of annual scale. We observe that the results obtained from SHAP align with the physical model interpretations, thus suggesting the need to add climatic variables as predictors in the prediction model.
Studies relating to trends of vegetation, snowfall and temperature in the north-western Himalayan region of India are generally focused on specific areas. Therefore, a proper understanding of regional changes in climate parameters over large time periods is generally absent, which increases the complexity of making appropriate conclusions related to climate change-induced effects in the Himalayan region. This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological records and simulated global climate data. Additionally, regression using machine learning algorithms such as Support Vectors and Long Short-term Memory (LSTM) network is carried out to check the possibility of predicting these environmental variables. Results from 17 years of data show an increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon since 2001. Solar radiation and cloud cover largely control the lapse rate variations. Mean MODIS-derived land surface temperature (LST) observations are in close agreement with global climate data. Future studies focused on climate trends and environmental parameters in Uttarakhand could fairly rely upon the remotely sensed measurements and simulated climate data for the region.
In the twenty-first century, climate change is emerging as a significant threat to the health and well-being of the public through links to the following: extreme weather events, sea level rise, temperature-related illnesses, air pollution patterns, water security, food security, vector-borne infectious diseases, and mental health effects (as a result of extreme weather events and climate change-induced population displacement). This article discusses how national healthcare systems can be redesigned through changes in its components such as human resources, facilities and technology, health information system, and health policy to meet these challenges.
The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (-9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth's climate.
Studies reveal that climate change (CC) has higher negative impacts on agricultural production than positive impacts. Therefore, this article attempts to explore the impacts of CC on oil palm production in Malaysia and provides mitigation and adaptation strategies towards reducing such impacts. The multiple regression analysis is applied to assess the impacts of CC on oil palm production by using time series data in the period of 1980 to 2010. A negative and significant relationship is found between annual average temperature and oil palm production. If temperature rises by 1 °C, 2 °C, 3 °C, and 4 °C, production of oil palm can decrease from a range of 10 to 41%. This article has also found a negative impact of sea level rise (SLR) on oil palm production. Findings reveal that if areas under oil palm production decrease by 2%, 4%, and 8% due to SLR of 0.5, 1, and 2 m, oil palm production can decrease by 1.98%, 3.96%, and 7.92%, respectively, indicating that CC has a significant impact on the reduction of oil palm production in Malaysia, ultimately affecting the sustainability of oil palm sector in Malaysia. Finally, this study suggests to practice appropriate mitigation and adaptation strategies, including promotion and development of climate resilient varieties, soil and water conservation, afforestation, insurance and other risk transfer mechanisms, emission reduction technology, protection of coastal flooding for reducing the impacts of CC on oil palm production.
Diversifying selection between populations that inhabit different environments can promote lineage divergence within species and ultimately drive speciation. The mitochondrial genome (mitogenome) encodes essential proteins of the oxidative phosphorylation (OXPHOS) system and can be a strong target for climate-driven selection (i.e., associated with inhabiting different climates). We investigated whether Pleistocene climate changes drove mitochondrial selection and evolution within Australian birds. First, using phylogeographic analyses of the mitochondrial ND2 gene for 17 songbird species, we identified mitochondrial clades (mitolineages). Second, using distance-based redundancy analyses, we tested whether climate predicts variation in intraspecific genetic divergence beyond that explained by geographic distances and geographic position. Third, we analysed 41 complete mitogenome sequences representing each mitolineage of 17 species using codon models in a phylogenetic framework and a biochemical approach to identify signals of selection on OXPHOS protein-coding genes and test for parallel selection in mitolineages of different species existing in similar climates. Of 17 species examined, 13 had multiple mitolineages (range: 2-6). Climate was a significant predictor of mitochondrial variation in eight species. At least two amino acid replacements in OXPHOS complex I could have evolved under positive selection in specific mitolineages of two species. Protein homology modelling showed one of these to be in the loop region of the ND6 protein channel and the other in the functionally critical helix HL region of ND5. These findings call for direct tests of the functional and evolutionary significance of mitochondrial protein candidates for climate-associated selection.
Palms are iconic plants. Oil palms are very important economically and originate in Africa where they can act as a model for palms in general. The effect of future climate on the growth of oil palm will be very detrimental. Latitudinal migration of tropical crops to climate refuges may be impossible, and longitudinal migration has only been confirmed for oil palm, of all the tropical crops. The previous method to determine the longitudinal trend for oil palm used the longitudes of various countries in Africa and plotted these against the percentage suitable climate for growing oil palms in each country. An increasing longitudinal trend was observed from west to east. However, the longitudes of the countries were randomly distributed which may have introduced bias and the procedure was time consuming. The present report presents an optimised and systematic procedure that divided the regions, as presented on a map derived from a CLIMEX model, into ten equal sectors and the percentage suitable climates for growing oil palm were determined for each sector. This approach was quicker, systematic and straight forward and will be useful for management of oil palm plantations under climate change. The method confirmed and validated the trends reported in the original method although the suitability values were often lower and there was less spread of values around the trend. The values for the CSIRO MK3.0 and MIROC H models demonstrated considerable similarities to each other, contributing to validation of the method. The procedure of dividing maps equally into sectors derived from models, could be used for other crops, regions, or systems more generally, where the alternative may be a more superficial visual examination of the maps. Methods are required to mitigate the effects of climate change and stakeholders need to contribute more actively to the current climate debate with tangible actions.
Palms are highly significant tropical plants. Oil palms produce palm oil, the basic commodity of a highly important industry. Climate change from greenhouse gasses is likely to decrease the ability of palms to survive, irrespective of them providing ecosystem services to communities. Little information about species survival in tropical regions under climate change is available and data on species migration under climate change is important. Palms are particularly significant in Africa: a palm oil industry already exists with Nigeria being the largest producer. Previous work using CLIMEX modelling indicated that Africa will have reduced suitable climate for oil palm in Africa. The current paper employs this modelling to assess how suitable climate for growing oil palm changed in Africa from current time to 2100. An increasing trend in suitable climate from west to east was observed indicating that refuges could be obtained along the African tropical belt. Most countries had reduced suitable climates but others had increased, with Uganda being particularly high. There may be a case for developing future oil palm plantations towards the east of Africa. The information may be usefully applied to other palms. However, it is crucial that any developments will fully adhere to environmental regulations. Future climate change will have severe consequences to oil palm cultivation but there may be scope for eastwards mitigation in Africa.
The impact of global warming has received much international attention in recent decades. To meet climate-change mitigation targets, environmental policy instruments have been designed to transform the way goods and services are produced as well as alter consumption patterns. The government of Malaysia is strongly committed to reducing CO2gas emissions as a proportion of GDP by 40% from 2005 levels by the year 2020. This study evaluates the economy-wide impacts of implementing two different types of CO2emission abatement policies in Malaysia using market-based (imposing a carbon tax) and command-and-control mechanism (sectoral emission standards). The policy simulations conducted involve the removal of the subsidy on petroleum products by the government. A carbon emission tax in conjunction with the revenue neutrality assumption is seen to be more effective than a command-and-control policy as it provides a double dividend. This is apparent as changes in consumption patterns lead to welfare enhancements while contributing to reductions in CO2emissions. The simulation results show that the production of renewable energies is stepped up when the imposition of carbon tax and removal of the subsidy is augmented by revenue recycling. This study provides an economy-wide assessment that compares two important tools for assisting environment policy makers evaluate carbon emission abatement initiatives in Malaysia.
The impact of global warming presents an increased risk to the world's shorelines. The Intergovernmental Panel on Climate Change (IPCC) reported that the twenty-first century experienced a severe global mean sea-level rise due to human-induced climate change. Therefore, coastal planners require reasonably accurate estimates of the rate of sea-level rise and the potential impacts, including extreme sea-level changes, floods, and shoreline erosion. Also, land loss as a result of disturbance of shoreline is of interest as it damages properties and infrastructure. Using a nonlinear autoregressive network with an exogenous input (NARX) model, this study attempted to simulate (1991 to 2012) and predict (2013-2020) sea-level change along Merang kechil to Kuala Marang in Terengganu state shoreline areas. The simulation results show a rising trend with a maximum rate of 28.73 mm/year and an average of about 8.81 mm/year. In comparison, the prediction results show a rising sea level with a maximum rate of 79.26 mm/year and an average of about 25.34 mm/year. The database generated from this study can be used to inform shoreline defense strategies adapting to sea-level rise, flood, and erosion. Scientists can forecast sea-level increases beyond 2020 using simulated sea-level data up to 2020 and apply it for future research. The data also helps decision-makers choose measures for vulnerable shoreline settlements to adapt to sea-level rise. Notably, the data will provide essential information for policy development and implementation to facilitate operational decision-making processes for coastal cities.