Accepted Manuscripts

Free trade and environmental sustainability are currently top economic and environmental research priorities. While numerous theories connect trade openness with environmental quality, empirical evidence often fails to support these claims. Using data spanning from 1980 to 2020, our study examines the effect of trade openness on CO2 emissions in South Africa. By employing a novel ARDL modeling framework, our analysis confirms the presence of the Environmental Kuznets Curve (EKC) hypothesis in South Africa. Our findings reveal that while GDP square enhances environmental quality, trade openness and economic growth have a degrading effect over time. Additionally, the study identifies that energy consumption, FDI, and value-added activities all contribute to environmental degradation. Findings also highlights the influence of institutional quality on the environment, demonstrating that political stability and control of corruption lead to increased CO2 emissions, while the rule of law reduces CO2 emissions. The research suggested that the potential of green economies should be leveraged in developing renewable energy, sustainable development, the recycling industry, and green financing sectors. A shift in economic activity in this direction will thus foster long-term economic growth and sustainable development.

Currently, the issue of eutrophication and cyanobacterial blooms persists in water bodies worldwide, prompting the exploration of various treatment methods. This study conducted a comparative analysis of eutrophic water bodies using ferric chloride-modified zeolite (FMZ) and calcium hydroxide-modified zeolite (CMZ) combined with Elodeanuttallii (E. nuttallii) for removal and purification effects. The results revealed that the addition of E. nuttallii had a sustained inhibitory effect on phosphorus release, maintaining stability with lower Turbidity(Tur) and stabilized pH within the range of 8.5-9. FMZ demonstrated rapid reduction in dissolved phosphorus concentration, achieving a removal rate of 96% within 3 days. The combined plant group of CMZ and FMZ exhibited synergistic effects with E. nuttallii, achieving an impressive total phosphorus (TP) removal rate of 80.13% and a total nitrogen (TN) removal rate of 48.77%. Additionally, chlorophyll a (Chl a) concentration decreased from 100.74 ± 24.72 μg/L to 49.96 ± 2.08 μg/L. The phytoplankton community composition indicated that diatoms thrived in low temperatures and high NH4 conditions. Under the same low Total Nitrogen to Total Phosphorus (TN:TP) ratio, high TP concentrations were associated with cyanobacteria dominance, while green algae dominated in other scenarios. This comprehensive approach demonstrates the potential efficacy of CMZ and FMZ combined with E. nuttallii in addressing eutrophic water bodies and mitigating cyanobacterial blooms.

Anthropogenic carbon dioxide (CO2) is penetrating up to 1000 m of water column in the Indian Ocean resulting in acidification and corrosion of aragonite skeletal material. The shallowest aragonite saturation horizon (ASH) was observed in the Bay of Bengal (BoB; 219±10 m) within the tropical Indian Ocean. The ASH shoaled at the rate of 6.3±5 and 4.4±3 m yr-1 in the past four decades in the BoB and Arabian Sea respectively. As a result, an increase in total alkalinity (TA) was observed at the rate of 0.5±0.3 and 0.25±0.2 mol kg-1 yr-1 at the depth of ASH in the BoB, and Arabian Sea respectively. While shoaling rate of ASH remained same in the Arabian Sea over past four decades, in contrast, the rapid shoaling was observed in the BoB in the recent decades due to higher accumulation of anthropogenic CO2 in the upper ocean associated with an increase in river discharge and decomposition of riverine organic matter. These two processes decreased the pH resulting in corrosion of aragonite skeletal material and increased TA at the depth of ASH in the BoB. Under a business-as-usual scenario, aragonite-secreting organisms will be seriously affected by the middle of this century in the BoB.

Hot extremes, such as heatwaves, have been associated with health, economic, and ecosystem-wide impacts. The timing of emergence of changes in extremes due to anthropogenic climate change is a topic of broad scientific and societal importance. While various studies have estimated the timing and impacts of heatwaves, the definitional aspect of a heatwave in determining the relative time of emergence has not been addressed. We adopt two commonly used definitions of heatwave employed in different reports of the Intergovernmental Panel on Climate Change (IPCC) to evaluate the time at which the frequency of heatwaves becomes detectably different from the historical baseline using an ensemble of 10 GCMS from the CMIP6 archives forced by the SSP2-4.5 concentration pathway. For a heat wave definition of sustained temperatures exceeding 5°C warmer above the historical climatology, time of emergence is earliest in high latitudes over land and displays correlation with the signal (amount of warming) and noise (variability). In contrast, for a heat wave definition of sustained temperatures exceeding the 90th percentile of historical climatology, time of emergence is earliest in low latitude regions and is correlated with the signal to noise ratio. This work underscores the importance of metric choice in estimating the timing of new climate regimes and that metric selection for informing adaptation timing should thus be tailored to the regional context.

Although durable goods with low energy consumption are being promoted to achieve a decarbonised society, from the perspective of life-cycle assessment, the choice of new durable goods may increase CO2 emissions. To address this problem, research has been conducted on product replacement based on life-cycle optimisation (LCO), a method for identifying a replacement life span that minimises life-cycle CO2 emissions. However, several additional assumptions complicate the analysis of replacement patterns of products and conditional formulas because cumulative emissions do not increase linearly when considering energy mix and technology improvement, and it is difficult to extend the model to optimisation methods in previous LCO studies. This study developed a new LCO approach by applying the shortest path problem to graph theory. Our methodology can contribute to the following: (i) it is computationally inexpensive; (ii) it is intuitively easy to add complex conditions, such as various policy scenarios and parameter changes; and (iii) once the graph of replacement patterns is defined, the optimal solution can be derived using existing solution methods, such as the Dijkstra algorithm. As a case study, we focused on vehicle replacement, which is a major source of CO2 emissions and is being electrified. In particular, we identified vehicle switching paths that minimise life-cycle CO2 emissions by considering changes in Japan's energy mix and alternative fuel vehicle (AFV) characteristics. We determined that the optimal vehicle replacement path method to reduce CO2 emissions is to switch first to plug-in hybrid electric vehicles (PHEVs) and then to battery electric vehicles (BEVs). Thus, we suggest that the transition to electric vehicles requires a step-by-step process. This methodology is not only conducive to AFV deployment for decarbonisation but can also be applied to other products, such as air conditioners and lighting. Thus, various transition policies could be formulated using our methodology.

Improving urban land green use efficiency (ULGUE) is essential for achieving the sustainable use of land resources and the high-quality economic development of cities. The digital economy has overcome spatial and locational constraints, blurred the boundaries between industries, and created a collaborative and open economic model, inevitably affecting urban land utilization. However, whether the digital economy will affect ULGUE and how such an effect would take place are still unclear. This study evaluates the digital economy and ULGUE of Chinese cities from 2011 to 2019 and systematically analyzes both the direct and indirect impact mechanisms through which the digital economy affects ULGUE. The results show that the digital economy can significantly enhance ULGUE, and these results prove to be reliable, as shown by various endogeneity treatments and robustness tests. The digital economy enhances ULGUE by optimizing the industrial structure (structural effect), increasing green technology innovation (technical effect), and agglomerating digital talent (scale effect). Moreover, land finance dependency plays an adverse moderating role in the relationship between the digital economy and ULGUE. Further heterogeneity analysis shows that the promoting effect of the digital economy on ULGUE takes full effect in the eastern cities, larger cities, and cities with high levels of digital economy development and land marketization. This paper presents recommendations for supporting the balanced and integrated development of the digital economy across regions and provides differentiated development strategies to enhance ULGUE in the context of digitization.

The unique in-situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice process. Cloud base droplet number concentration is about 142±79 cm-3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2 % supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion (ε; the ratio of DSD spectral width (σ) to mean radius (r_m)) and liquid water adiabatic fraction (AF) indicates that entrainment effect has increased relative dispersion significantly (2-3 times larger) in these clouds. Effective radius (r_eff) is found to be proportional to mean volume radius (r_v) with a proportionality constant (β) that varies between 1.0-1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2-50 μm and the large drizzle drops (or ice hydrometeors) with size range 100-6400 μm are parameterized using the gamma function distributions useful for large-scale cloud models.

Since the early 2000s, Ca Mau has experienced a rapid boom in shrimp farming, leading to the conversion of mangroves into shrimp ponds and impeding mangrove forest conservation. Despite its negative environmental impacts, shrimp aquaculture remains vital to Ca Mau's economy by providing employment opportunities and contributing to the province's gross domestic product. This study constructed a system dynamic model to analyze the complex system of shrimp aquaculture and mangrove forests under two development scenarios: the Business-as-Usual (BAU) scenario and the Policy scenario. In the BAU scenario, shrimp aquaculture will continue to expand, resulting in the conversion of more mangroves into ponds and a decrease in Ca Mau's mangrove forest to 70,349 (± 888.801) hectares in 2050. However, this expansion will bolster rural employment and the province's economy, generating 14,250 (± 0.336) billion VND (US$ 570 million) in 2050. Conversely, in the Policy scenario, stabilizing shrimp areas at 280,000 hectares as a policy target will regulate mangrove conversion, allowing mangroves to regenerate (77,016 (± 687.155) hectares in 2050) and enhancing carbon storage (65x10^6 (± 0.58x10^6) MgC in 2050). However, challenges arise in the Policy scenario concerning potential economic stagnation, conflicts with other development priorities, and rural job losses. Officials must consider more than just the area of shrimp ponds to achieve sustainable development. Effective land use strategies should be implemented to ensure equilibrium between shrimp aquaculture and mangroves. Diversifying economic activities and promoting alternative livelihoods can mitigate the dependence on shrimp farming and offset the effects of policy interventions.

Citizen participation is key to learn of actors' lived experiences for the design of just energy policies. Many members of society, however, experience barriers to participation. As a result, the injustices they experience are likely to remain hidden from public decision-making processes. This paper applies the "hidden morality" framework to a case study of migrants with a low socio-economic status (SES) in the Dutch city of The Hague. Through the analysis of 15 policy documents and 26 semi-structured interviews with migrants in a low-SES neighbourhood, this paper uncovers hidden injustices and the societal mechanisms forming barriers to participation. Simultaneously, the case study is used to test the conceptual framework. The study reveals that the interviewed low-SES migrants were not only considerably prevented from expressing their perceived injustices in decision-making, but were also unaware that they were subject to several procedural injustices. We identify three main barriers withholding low-SES migrants from participating in decision-making: unfamiliarity with (Dutch) democratic institutions and of their rights as citizens; language barriers; and weak social ties in their neighbourhoods. We conclude that the hidden morality framework proves useful for revealing injustices and barriers to participation that would otherwise run the risk of remaining hidden from scholars and policymakers.

The future projected frequency of a specified baseline extreme sea level (ESL), often called the amplification factor (AF), is extensively used as a metric of evolving coastal flood hazard with sea level rise (SLR). The baseline ESL is typically analyzed using extreme value analysis, and the SLR is added to the resulting distribution. In the presence of SLR uncertainty, it is natural to analyze AFs probabilistically. I derive probability density functions (PDFs) of AF, given uncertainty distributions of SLR. If the ESL distribution is modeled as Gumbel and the SLR distribution as normal, then the AF distribution is log normal. However, in active tropical cyclone regions, ESL often has a longer tail than Gumbel, and a Frechet (Type-II) Generalized Extreme Value (GEV) is more appropriate. In this case, I show that the AF distribution has a divergent mean, preventing its use as a hazard metric. In addition, I show that for Frechet ESL, the AF cannot even be defined for SLR above a threshold (β/ξ) f_0^(-ξ), where f0 is the specified baseline frequency (e.g., f0 = 0.01 yr-1 for the 100-year exceedance),  is the GEV scale parameter and  the shape parameter. This SLR threshold can be as low as 0.5m in the southeast US and Caribbean, within reach mid to late century. Above the threshold, ESL at all frequencies exceeds the baseline reference frequency, preventing the calculation of AF. The resulting probabilistic distribution of AF is insensitive to SLR above the threshold. These features detrimentally impact the utility of AF as a hazard metric. Frechet distributions are appropriate and commonly used for ESL in tropical cyclone regions, but AFs applied to such distributions must interpreted with caution. In such regions, coastal risk managers should consider other flood hazard metrics, such as probabilistic estimates of flood depth.