Transboundary air pollution and cross-border cooperation: Insights from marine vessel emissions regulations in Hong Kong and Shenzhen

Kim, Seung Kyum; Gevelt, Terry van; Joosse, Paul; Bennett, Mia M.

doi:10.1016/j.scs.2022.103774

Cited by 14 publications

(4 citation statements)

References 37 publications

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“…The result could be driven by cross-border pollution as Jakarta is surrounded by outskirt areas such as Bogor, Depok, Tangerang, Bekasi, Karawang (8) as urban agglomeration cluster that still had a high intensity of industrial, commercial, office work, transportation and domestic activity during the pandemics 2020-2021 (26). The result is supported by similar findings from other cities, for instance, aerosols air pollutants generated from mainland China reached Japan after few hours, and it was supported by the favourable wind direction and meteorological condition (27). While emission binding policy cooperation between Hong Kong and Shenzhen was found substantially could minimize transboundary air pollution in both countries (28).…”

Section: Cross Correlation Analysismentioning

confidence: 61%

Profiling Temporal Pattern of Particulate Matter (PM10) and Meteorological Parameters in Jakarta Province during 2020-2021

Husnina

Wangdi²,

Puspita³

et al. 2023

JKL

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Introduction: Jakarta has recorded heightened air pollution for years, and particulate matter (PM10) is one of the pollutants that could bring health burden in population. This study described the distribution of PM10 as well as analysed the correlation with meteorological parameters during 2020–2021 in Jakarta Province. Methods: Air quality standard index daily data from January 1st 2020 to March 31st 2021 was retrieved from the official data portal (https://data.jakarta.go.id/). The Spearman Rank correlation was employed to understand the correlation between PM10 Index with meteorological factors. Autoregressive Integrative Moving Average (ARIMA) model was constructed and Akaike Information Criterion (AIC) selected the model. Cross-correlation analysis explored the association between PM10 with meteorological parameters at multiple time lags. Results and Discussion: PM10 Index started to increase in April 2020 and reached its peak in August 2020. PM10 was positively correlated with temperature (p-value <0.05, R2: 0.134), but it was negatively correlated with humidity and wind speed (p-value <0.05, R2: -0.392 and -0.129). The high cross-correlation coefficients were found between PM10 and temperature at lag 0, humidity at lag 1 and wind speed at lag 1 (rho: 0.42, -0.38 and -0.24). The time series model ARIMA with parameter (p,d,q) (1,1,1) describes the fluctuation of PM10 index data with AIC 3552.75. Conclusion: PM10 concentration in Jakarta is significantly correlated with meteorological factors. The implementation of social restriction in Jakarta need to be supported by pollution control in the neighbouring areas in order to be able to reduce PM10 pollution level.

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Section: Cross Correlation Analysismentioning

confidence: 61%

Profiling Temporal Pattern of Particulate Matter (PM10) and Meteorological Parameters in Jakarta Province during 2020-2021

Husnina

Wangdi²,

Puspita³

et al. 2023

JKL

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“…The cultivation of these strategic nodes also promotes the networked and multi-centralized development of cities. On the other hand, from a regional perspective, the networked layout of rapid transportation has led to the continuous emergence of cross-border cooperation models between different cities [18][19][20]. The cultivation of strategic space for CIPs has become an important platform for the exchange and cooperation of elements between different cities.…”

Section: Cip and "Enclave Economy"mentioning

confidence: 99%

Cross-Regional Cooperation and Counter-Market-Oriented Spatial Linkage: A Case Study of Collaborative Industrial Parks in the Yangtze River Delta Region

Wang

Liu

et al. 2023

IJERPH

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At present, collaborative industrial parks (CIPs) in the Yangtze River Delta Region (YRDR) have become an important spatial strategy for coordinating regional development. However, existing studies tend to focus on individualized micro-studies, ignoring the regional-scale production space reconstruction by the geographical expansion of CIPs. Based on this, this study takes the YRDR, where the development of CIPs is relatively mature, as an example and systematically analyzes their geographic expansion process and driving mechanism. The results found that CIPs in the YRDR have gone through three stages：the exploration period of CIP construction under the guidance of assistance policies; the blowout development period of CIPs under the demonstration effect; and the complete cluster formation period of CIPs. Regional central cities, such as Suzhou, Hangzhou, Nanjing, and underdeveloped cities, such as Tongling and Xuancheng, are core nodes, with Shanghai–Nantong; Shanghai–Anqing; Nanjing–Huainan; Wuxi–Xuzhou; Suzhou–Suqian; and Jiaxing–Lishui being important elements in the flow channel. The CIP network is basically formed. During this period, the degree of all nodes increased to 134, the network connection rate increased to 2.26, and the network complexity was more significant. Furthermore, CIPs are essentially a form of capital re-territorialization and space restoration organized and coordinated by the government (provincial government or central government). In the meantime, the market and the social environment, such as residents’ living standards, urban development foundation, urban transportation, and urban investment, also have an important impact on the geographic expansion of CIPs. In the regression results, the coefficients of popu, finance, labor, and passenger are significantly negative, but the coefficients of wage, gdp, freight, and govrd are significantly positive.

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“…The Regression Discontinuity Design (RDD) was used in this study to evaluate the environmental governance effect of the conversion of the driving forces of economic growth. The RDD has been widely used in air pollution literature, including taking time as a breakpoint to investigate whether there is a sudden change before and after a shock event [13][14][15][16]. The basic idea of Regression Discontinuity Design (RDD) is that there is a continuous variable, and under the influence of a certain exogenous shock policy, the continuous variable gets different treatment probabilities on both sides of the critical point, which also fits the purpose of this paper, and this idea is the reason for adopting the RDD in this paper.…”

Section: Econometric Equationsmentioning

confidence: 99%

Impact of New and Old Driving Force Conversion on Air Quality: Empirical Analysis Based on RDD

Zhu

Zhang

2023

Sustainability

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This paper evaluates the impact of the conversion of new and old driving forces of economic growth on air quality. Based on the policy shock of the establishment of the Shandong pilot zone, this paper took the monthly air quality index (AQI) as a measurement indicator and adopted the Regression Discontinuity Design (RDD) method. It was found that the conversion of new and old driving forces significantly improved air quality, and this effect was still robust for different bandwidths. The examination of individual pollutants revealed that the improvement in air quality (AQI) came mainly from the reduction in the levels of five pollutants in the air: PM2.5, PM10, SO2, CO, and NO2. Moreover, through the convergence analysis, it was found that the air pollution governance effect of the conversion of new and old driving forces had significant β convergence characteristics. The convergence characteristics were still robust even considering control variables and spatial factors, thus indicating that the conversion of new and old driving forces had a synergistic governance effect on air pollution control.

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Transboundary air pollution and cross-border cooperation: Insights from marine vessel emissions regulations in Hong Kong and Shenzhen

Cited by 14 publications

References 37 publications

Profiling Temporal Pattern of Particulate Matter (PM10) and Meteorological Parameters in Jakarta Province during 2020-2021

Profiling Temporal Pattern of Particulate Matter (PM10) and Meteorological Parameters in Jakarta Province during 2020-2021

Cross-Regional Cooperation and Counter-Market-Oriented Spatial Linkage: A Case Study of Collaborative Industrial Parks in the Yangtze River Delta Region

Impact of New and Old Driving Force Conversion on Air Quality: Empirical Analysis Based on RDD

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