Detecting Non-negligible New Influences in Environmental Data via a General Spatio-temporal Autoregressive Model
Journal Title: International Journal of Environment and Climate Change - Year 2017, Vol 7, Issue 4
Abstract
In some environmental problems, it is required to find out if new influences (e.g., new influences on the ozone concentration) occurred in one area of the region (named as a treatment area) have affected the measurements there substantially. For convenience, the area of the region that is free of influences is named as the control area. To tackle such problems, we propose a change-point detection approach. We first introduce a general spatio-temporal autoregressive (GSTAR) model for the environmental data, which takes into account effects of different spatial location surroundings, seasonal cyclicities, temporal correlations among observations at the same locations and spatial correlations among observations from different locations. An EM-type algorithm is provided for estimating the parameters in a GSTAR model. We then respectively model the data collected from the treatment and control areas of the region by the GSTAR models. If new influences occurred in the treatment area are not negligible, there should be detectable changes in the time-dependent regression coefficients in the GSTAR model for that area compared to those in the GSTAR model for the control area. A change-point detection method can be applied to the differences of regression coefficient estimates of these two models. We illustrate our method through one real data example of daily ozone concentration measurements and one simulated data example with two scenarios.
Authors and Affiliations
Yuehua Wu, Xiaoying Sun, Elton Chan, Shanshan Qin
Keywords
Related Articles
- EP ID EP350501
- DOI 10.9734/BJECC/2017/37044
- Views 142
- Downloads 0
Mitigating Greenhouse Gas and Ammonia Emissions from Stored Slurry through the Addition of Brewing Sugar and a Biological Additive
Livestock slurry stores are a key source of ammonia (NH3) and greenhouse gas (GHG) emissions. This study evaluated the potential to reduce NH3, CO2, CH4 and N2O emissions by adding effective microorganisms (EM) and brewi...
How Does Your Garden Flow? The Impact of Domestic Front Gardens on Urban Flooding
Aims: To quantify rainwater runoff from domestic front gardens as a consequence of increased impervious surface area and climate change impacts, thus allowing the runoff contribution from both newly and previously covere...
Utilising Time of Use Surveys to Predict Domestic Hot Water Consumption and Heat Demand Profiles of Residential Building Stocks
Aims: The prediction of water consumption patterns is a challenge, especially when water metering is not available at scale. The use of time-of-use survey (TUS) data offers an alternative to metering in order to track th...
Carrying Capacity and Sustainability Appraisals on Regional Water Supply Systems under Climate Change
This study aims to appraise the carrying capacity and sustainability of four water supply systems which are in the same watershed under climate change. An integrated assessment tool, TaiWAP, which integrates the common p...
Climate Change Diplomacy- Apparatus for Climate Change Mitigation and Adaptation: A Reflection in the Context of Bangladesh
The objective of this analysis is mainly to examine the current trend of climate change diplomacy carry forward by the Government of Bangladesh. This focus on effectiveness of Climate Change (CC) Diplomacy for the climat...